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        <title>Journal of Bioinformatics and Computational Biology via MedWorm.com</title>
        <description>MedWorm.com provides a medical RSS filtering service. Over 6000 RSS medical sources are combined and output via different filters. This feed contains the latest items from the 'Journal of Bioinformatics and Computational Biology' source.</description>
        <link><![CDATA[http://www.medworm.com/rss/search.php?qu=Journal+of+Bioinformatics+and+Computational+Biology&t=Journal+of+Bioinformatics+and+Computational+Biology&s=Search&f=source]]></link>
        <lastBuildDate>Sat, 28 Jan 2012 00:35:47 +0100</lastBuildDate>
        <item>
            <title>Introduction. Progresses in genome informatics.</title>
            <link>http://www.medworm.com/index.php?rid=5619612&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D22144256%26dopt%3DAbstract</link>
            <description>Authors: Chu IS, Gotoh O, Lee I
    PMID: 22144256 [PubMed - in process] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5619612</comments>
            <pubDate>Thu, 01 Dec 2011 05:00:00 +0100</pubDate>
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        <item>
            <title>Introduction--some new results and tools for protein function prediction, RNA target site prediction, genotype calling, environmental genomics, and more.</title>
            <link>http://www.medworm.com/index.php?rid=5546609&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D22187755%26dopt%3DAbstract</link>
            <description>Authors: Wong L
    PMID: 22187755 [PubMed - in process] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5546609</comments>
            <pubDate>Thu, 01 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5546609</guid>        </item>
        <item>
            <title>Cscore: a simple yet effective scoring function for protein-ligand binding affinity prediction using modified cmac learning architecture.</title>
            <link>http://www.medworm.com/index.php?rid=5531003&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D22144250%26dopt%3DAbstract</link>
            <description>Authors: Ouyang X, Handoko SD, Kwoh CK
    Abstract
    Protein-ligand docking is a computational method to identify the binding mode of a ligand and a target protein, and predict the corresponding binding affinity using a scoring function. This method has great value in drug design. After decades of development, scoring functions nowadays typically can identify the true binding mode, but the prediction of binding affinity still remains a major problem. Here we present CScore, a data-driven scoring function using a modified Cerebellar Model Articulation Controller (CMAC) learning architecture, for accurate binding affinity prediction. The performance of CScore in terms of correlation between predicted and experimental binding affinities is benchmarked under different validation approaches....</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5531003</comments>
            <pubDate>Thu, 01 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5531003</guid>        </item>
        <item>
            <title>Discovery and evaluation of potential sonic hedgehog signaling pathway inhibitors using pharmacophore modeling and molecular dynamics simulations.</title>
            <link>http://www.medworm.com/index.php?rid=5531002&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D22144251%26dopt%3DAbstract</link>
            <description>This study was done in order to develop a lead chemical candidate that has an inhibitory function in the Shh signaling pathway. We have generated common feature pharmacophore models using three-dimensional (3D) structural information of robotnikinin, an inhibitor of the Shh signaling pathway, and its analogs. These models have been validated with fit values of robotnikinin and its analogs, and the best model was used as a 3D structural query to screen chemical databases. The hit compounds resulted from the screening docked into a proposed binding site of the Shh named pseudo-active site. Molecular dynamics (MD) simulations were performed to investigate detailed binding modes and molecular interactions between the hit compounds and functional residues of the pseudo-active site. The results ...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5531002</comments>
            <pubDate>Thu, 01 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5531002</guid>        </item>
        <item>
            <title>Folding elastic transmembrane helices to fit in a low-resolution image by electron microscopy.</title>
            <link>http://www.medworm.com/index.php?rid=5531001&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D22144252%26dopt%3DAbstract</link>
            <description>Authors: Ueno Y, Kawasaki K, Saito O, Arai M, Suwa M
    Abstract
    Structure prediction of membrane proteins could be constrained and thereby improved by introducing data of the observed molecular shape. We studied a coarse-grained molecular model that relied on residue-based dummy atoms to fold the transmembrane helices of a protein in the observed molecular shape. Based on the inter-residue potential, the α-helices were folded to contact each other in a simulated annealing protocol to search optimized conformation. Fitting the model into a three-dimensional volume was tested for proteins with known structures and resulted in a fairly reasonable arrangement of helices. In addition, the constraint to the packing transmembrane helix with the two-dimensional region was tested and found t...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5531001</comments>
            <pubDate>Thu, 01 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5531001</guid>        </item>
        <item>
            <title>Srmbuilder: a user-friendly tool for selected reaction monitoring data analysis.</title>
            <link>http://www.medworm.com/index.php?rid=5531000&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D22144253%26dopt%3DAbstract</link>
            <description>Authors: Sheng Q, Wu C, Su Z, Zeng R
    Abstract
    With high sensitivity and reproducibility, selected reaction monitoring (SRM) has become increasingly popular in proteome research for targeted quantification of low abundance proteins and post translational modification. SRM is also well accepted in other mass-spectrometry based research areas such as lipidomics and metabolomics, which necessitates the development of easy-to-use software for both post-acquisition SRM data analysis and quantification result validation. Here, we introduce a software tool SRMBuilder, which can automatically parse SRM data in multiple file formats, assign transitions to compounds, match light/heavy transition/compound pairs and provide a user-friendly graphic interface to manually validate the quantificati...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5531000</comments>
            <pubDate>Thu, 01 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5531000</guid>        </item>
        <item>
            <title>A transcriptome analysis by lasso penalized cox regression for pancreatic cancer survival.</title>
            <link>http://www.medworm.com/index.php?rid=5530999&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D22144254%26dopt%3DAbstract</link>
            <description>Authors: Wu TT, Gong H, Clarke EM
    Abstract
    Pancreatic cancer is the fourth leading cause of cancer deaths in the United States with five-year survival rates less than 5% due to rare detection in early stages. Identification of genes that are directly correlated to pancreatic cancer survival is crucial for pancreatic cancer diagnostics and treatment. However, no existing GWAS or transcriptome studies are available for addressing this problem. We apply lasso penalized Cox regression to a transcriptome study to identify genes that are directly related to pancreatic cancer survival. This method is capable of handling the right censoring effect of survival times and the ultrahigh dimensionality of genetic data. A cyclic coordinate descent algorithm is employed to rapidly select the most...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5530999</comments>
            <pubDate>Thu, 01 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5530999</guid>        </item>
        <item>
            <title>Inference of s-system models of gene regulatory networks using immune algorithm.</title>
            <link>http://www.medworm.com/index.php?rid=5530998&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D22144255%26dopt%3DAbstract</link>
            <description>Authors: Nakayama T, Seno S, Takenaka Y, Matsuda H
    Abstract
    The S-system model is one of the nonlinear differential equation models of gene regulatory networks, and it can describe various dynamics of the relationships among genes. If we successfully infer rigorous S-system model parameters that describe a target gene regulatory network, we can simulate gene expressions mathematically. However, the problem of finding an optimal S-system model parameter is too complex to be solved analytically. Thus, some heuristic search methods that offer approximate solutions are needed for reducing the computational time. In previous studies, several heuristic search methods such as Genetic Algorithms (GAs) have been applied to the parameter search of the S-system model. However, they have not a...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5530998</comments>
            <pubDate>Thu, 01 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5530998</guid>        </item>
        <item>
            <title>Sequential linear neighborhood propagation for semi-supervised protein function prediction.</title>
            <link>http://www.medworm.com/index.php?rid=5417793&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D22084007%26dopt%3DAbstract</link>
            <description>Authors: Wang J, Li Y
    Abstract
    Predicting protein function is one of the most challenging problems of the post-genomic era. The development of experimental methods for genome scale analysis of molecular interaction networks has provided new approaches to inferring protein function. In this paper we introduce a new graph-based semi-supervised classification algorithm Sequential Linear Neighborhood Propagation (SLNP), which addresses the problem of the classification of partially labeled protein interaction networks. The proposed SLNP first constructs a sequence of node sets according to their shortest distance to the labeled nodes, and then predicts the function of the unlabel proteins from the set closer to labeled one, using Linear Neighborhood Propagation. Its performance is asse...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5417793</comments>
            <pubDate>Fri, 18 Nov 2011 02:07:15 +0100</pubDate>
            <guid isPermaLink="false">5417793</guid>        </item>
        <item>
            <title>A graph-based semantic similarity measure for the gene ontology.</title>
            <link>http://www.medworm.com/index.php?rid=5417792&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D22084008%26dopt%3DAbstract</link>
            <description>Authors: Alvarez MA, Yan C
    Abstract
    Existing methods for calculating semantic similarities between pairs of Gene Ontology (GO) terms and gene products often rely on external databases like Gene Ontology Annotation (GOA) that annotate gene products using the GO terms. This dependency leads to some limitations in real applications. Here, we present a semantic similarity algorithm (SSA), that relies exclusively on the GO. When calculating the semantic similarity between a pair of input GO terms, SSA takes into account the shortest path between them, the depth of their nearest common ancestor, and a novel similarity score calculated between the definitions of the involved GO terms. In our work, we use SSA to calculate semantic similarities between pairs of proteins by combining pairwis...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5417792</comments>
            <pubDate>Fri, 18 Nov 2011 02:07:05 +0100</pubDate>
            <guid isPermaLink="false">5417792</guid>        </item>
        <item>
            <title>USING BINDING PROFILES TO PREDICT BINDING SITES OF TARGET RNAs.</title>
            <link>http://www.medworm.com/index.php?rid=5417791&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D22084009%26dopt%3DAbstract</link>
            <description>Authors: Poolsap U, Kato Y, Sato K, Akutsu T
    Abstract
    Prediction of RNA-RNA interaction is a key to elucidating possible functions of small non-coding RNAs, and a number of computational methods have been proposed to analyze interacting RNA secondary structures. In this article, we focus on predicting binding sites of target RNAs that are expected to interact with regulatory antisense RNAs in a general form of interaction. For this purpose, we propose bistaRNA, a novel method for predicting multiple binding sites of target RNAs. bistaRNA employs binding profiles that represent scores for hybridized structures, leading to reducing the computational cost for interaction prediction. bistaRNA considers an ensemble of equilibrium interacting structures and seeks to maximize expected acc...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5417791</comments>
            <pubDate>Fri, 18 Nov 2011 02:06:56 +0100</pubDate>
            <guid isPermaLink="false">5417791</guid>        </item>
        <item>
            <title>A new genotype calling method for affymetrix SNP arrays.</title>
            <link>http://www.medworm.com/index.php?rid=5417790&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D22084010%26dopt%3DAbstract</link>
            <description>Authors: Fu B, Xu J
    Abstract
    Current genotype-calling methods such as Robust Linear Model with Mahalanobis Distance Classifier (RLMM) and Corrected Robust Linear Model with Maximum Likelihood Classification (CRLMM) provide accurate calling results for Affymetrix Single Nucleotide Polymorphisms (SNP) chips. However, these methods are computationally expensive as they employ preprocess procedures, including chip data normalization and other sophisticated statistical techniques. In the small sample case the accuracy rate may drop significantly. We develop a new genotype calling method for Affymetrix 100 k and 500 k SNP chips. A two-stage classification scheme is proposed to obtain a fast genotype calling algorithm. The first stage uses unsupervised classification to quickly discrimina...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5417790</comments>
            <pubDate>Fri, 18 Nov 2011 02:06:47 +0100</pubDate>
            <guid isPermaLink="false">5417790</guid>        </item>
        <item>
            <title>Verification of phylogenetic inference programs using metamorphic testing.</title>
            <link>http://www.medworm.com/index.php?rid=5417789&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D22084011%26dopt%3DAbstract</link>
            <description>Authors: Sadi MS, Kuo FC, Ho JW, Charleston MA, Chen TY
    Abstract
    Many phylogenetic inference programs are available to infer evolutionary relationships among taxa using aligned sequences of characters, typically DNA or amino acids. These programs are often used to infer the evolutionary history of species. However, in most cases it is impossible to systematically verify the correctness of the tree returned by these programs, as the correct evolutionary history is generally unknown and unknowable. In addition, it is nearly impossible to verify whether any non-trivial tree is correct in accordance to the specification of the often complicated search and scoring algorithms. This difficulty is known as the oracle problem of software testing: there is no oracle that we can use to verify...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5417789</comments>
            <pubDate>Fri, 18 Nov 2011 02:06:38 +0100</pubDate>
            <guid isPermaLink="false">5417789</guid>        </item>
        <item>
            <title>Jaguc - a software package for environmental diversity analyses.</title>
            <link>http://www.medworm.com/index.php?rid=5417788&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D22084012%26dopt%3DAbstract</link>
            <description>Conclusions: The new program package JAGUC is a tool that bridges the gap between computational and biological sciences. It enables biologists to process large sequence data sets in order to infer biological meaning from hundreds of thousands of raw sequence data. JAGUC offers advantages over available tools which are further discussed in this manuscript.
    PMID: 22084012 [PubMed - in process] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5417788</comments>
            <pubDate>Fri, 18 Nov 2011 02:06:30 +0100</pubDate>
            <guid isPermaLink="false">5417788</guid>        </item>
        <item>
            <title>Comparison of two academic software packages for analyzing two-dimensional gel images.</title>
            <link>http://www.medworm.com/index.php?rid=5417787&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D22084013%26dopt%3DAbstract</link>
            <description>COMPARISON OF TWO ACADEMIC SOFTWARE PACKAGES FOR ANALYZING TWO-DIMENSIONAL GEL IMAGES.
    J Bioinform Comput Biol. 2011 Dec;9(6):775-794
    Authors: Wu Y, Zhang L
    Abstract
    One of the key limitations for proteomic studies using two-dimensional (2D) gel is the lack of automatic, fast, robust, and reliable methods for detecting, matching, and quantifying protein spots. Although there are commercial software packages for 2D gel image analysis, extensive human intervention is still needed for spot detection and matching, which is time-consuming and error-prone. Moreover, the commercial software packages are usually expensive and non-open source. Thus, it is very beneficial for researchers to have free software that is fast, fully automatic, and robust. In this paper, we review and com...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5417787</comments>
            <pubDate>Fri, 18 Nov 2011 02:06:20 +0100</pubDate>
            <guid isPermaLink="false">5417787</guid>        </item>
        <item>
            <title>How to choose a normalization strategy for mirna quantitative real-time (qpcr) arrays.</title>
            <link>http://www.medworm.com/index.php?rid=5417786&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D22084014%26dopt%3DAbstract</link>
            <description>In this study we present the comparison of a number of data-driven normalization methods for TaqMan low-density arrays for qPCR and different descriptive statistical techniques that can facilitate the choice of normalization method. The performance of the normalization methods was assessed and compared against each other as well as against standard normalization using endogenous controls. The results clearly show that the data-driven methods reduce variation and represent robust alternatives to using endogenous controls.
    PMID: 22084014 [PubMed - in process] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5417786</comments>
            <pubDate>Fri, 18 Nov 2011 02:06:12 +0100</pubDate>
            <guid isPermaLink="false">5417786</guid>        </item>
        <item>
            <title>Introduction--the First IEEE Conference on Healthcare Informatics, Imaging, and Systems Biology HISB'11.</title>
            <link>http://www.medworm.com/index.php?rid=5417794&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D22069831%26dopt%3DAbstract</link>
            <description>Authors: Chen XW, Miyano S
    PMID: 22069831 [PubMed - in process] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5417794</comments>
            <pubDate>Sat, 01 Oct 2011 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">5417794</guid>        </item>
        <item>
            <title>Sequence-based enzyme catalytic domain prediction using clustering and aggregated mutual information content.</title>
            <link>http://www.medworm.com/index.php?rid=5295201&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21976378%26dopt%3DAbstract</link>
            <description>Authors: Choi K, Kim S
    Abstract
    Characterizing enzyme sequences and identifying their active sites is a very important task. The current experimental methods are too expensive and labor intensive to handle the rapidly accumulating protein sequences and structure data. Thus accurate, high-throughput in silico methods for identifying catalytic residues and enzyme function prediction are much needed. In this paper, we propose a novel sequence-based catalytic domain prediction method using a sequence clustering and an information-theoretic approaches. The first step is to perform the sequence clustering analysis of enzyme sequences from the same functional category (those with the same EC label). The clustering analysis is used to handle the problem of widely varying sequence similarit...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5295201</comments>
            <pubDate>Sat, 01 Oct 2011 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">5295201</guid>        </item>
        <item>
            <title>Quantitative modeling of the Saccharomyces cerevisiae flr1 regulatory network using an s-system formalism.</title>
            <link>http://www.medworm.com/index.php?rid=5295200&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21976379%26dopt%3DAbstract</link>
            <description>In this study we address the problem of finding a quantitative mathematical model for the genetic network regulating the stress response of the yeast Saccharomyces cerevisiae to the agricultural fungicide mancozeb. An S-system formalism was used to model the interactions of a five-gene network encoding four transcription factors (Yap1, Yrr1, Rpn4 and Pdr3) regulating the transcriptional activation of the FLR1 gene. Parameter estimation was accomplished by decoupling the resulting system of nonlinear ordinary differential equations into a larger nonlinear algebraic system, and using the Levenberg-Marquardt algorithm to fit the models predictions to experimental data. The introduction of constraints in the model, related to the putative topology of the network, was explored. The results show...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5295200</comments>
            <pubDate>Sat, 01 Oct 2011 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">5295200</guid>        </item>
        <item>
            <title>A compressed sensing based approach for subtyping of leukemia from gene expression data.</title>
            <link>http://www.medworm.com/index.php?rid=5295199&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21976380%26dopt%3DAbstract</link>
            <description>Authors: Tang W, Cao H, Duan J, Wang YP
    Abstract
    With the development of genomic techniques, the demand for new methods that can handle high-throughput genome-wide data effectively is becoming stronger than ever before. Compressed sensing (CS) is an emerging approach in statistics and signal processing. With the CS theory, a signal can be uniquely reconstructed or approximated from its sparse representations, which can therefore better distinguish different types of signals. However, the application of CS approach to genome-wide data analysis has been rarely investigated. We propose a novel CS-based approach for genomic data classification and test its performance in the subtyping of leukemia through gene expression analysis. The detection of subtypes of cancers such as leukemia ac...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5295199</comments>
            <pubDate>Sat, 01 Oct 2011 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">5295199</guid>        </item>
        <item>
            <title>A systems biology approach for detecting toxicity-related hotspots inside protein interaction networks.</title>
            <link>http://www.medworm.com/index.php?rid=5295198&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21976381%26dopt%3DAbstract</link>
            <description>In this study, a human protein interaction network was analyzed to identify proteins that are most central to topological paths connecting a drug's target proteins to hematopoiesis-related proteins. For a set of non-immune neutropenia inducing drugs, 9 proteins were found to be common to putative signaling paths across all drugs evaluated. All 9 proteins showed relevance to neutrophil biology. Geneset enrichment analysis showed that proteins associated with cancer-related processes such as apoptosis provide topological linkages between drug targets and proteins involved in neutrophil production. The algorithm can be applied towards analysis of any toxicity where the drugs and the physiological processes involved in the toxic mechanism are known.
    PMID: 21976381 [PubMed - in process] (So...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5295198</comments>
            <pubDate>Sat, 01 Oct 2011 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">5295198</guid>        </item>
        <item>
            <title>Brief introduction to some new papers on lateral transfer reconstruction, drug candidate screening, disease gene identification, and other results.</title>
            <link>http://www.medworm.com/index.php?rid=5095656&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21776602%26dopt%3DAbstract</link>
            <description>BRIEF INTRODUCTION TO SOME NEW PAPERS ON LATERAL TRANSFER RECONSTRUCTION, DRUG CANDIDATE SCREENING, DISEASE GENE IDENTIFICATION, AND OTHER RESULTS.
    J Bioinform Comput Biol. 2011 Aug;9(4):v-vii
    Authors: Wong L
    No abstract received.
    PMID: 21776602 [PubMed - as supplied by publisher] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5095656</comments>
            <pubDate>Sun, 31 Jul 2011 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">5095656</guid>        </item>
        <item>
            <title>Identifying and reconstructing lateral transfers from distance matrices by combining the minimum contradiction method and neighbor-net.</title>
            <link>http://www.medworm.com/index.php?rid=5095651&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21776603%26dopt%3DAbstract</link>
            <description>Authors: Thuillard M, Moulton V
    Identifying lateral gene transfers is an important problem in evolutionary biology. Under a simple model of evolution, the expected values of an evolutionary distance matrix describing a phylogenetic tree fulfill the so-called Kalmanson inequalities. The Minimum Contradiction method for identifying lateral gene transfers exploits the fact that lateral transfers may generate large deviations from the Kalmanson inequalities. Here a new approach is presented to deal with such cases that combines the Neighbor-Net algorithm for computing phylogenetic networks with the Minimum Contradiction method. A subset of taxa, prescribed using Neighbor-Net, is obtained by measuring how closely the Kalmanson inequalities are fulfilled by each taxon. A criterion is then us...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5095651</comments>
            <pubDate>Sun, 31 Jul 2011 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">5095651</guid>        </item>
        <item>
            <title>Patterns of hydrophobicity found in the first and second transmembrane domains of solute transporters suggest a possible role in nascent protein anchoring and organization.</title>
            <link>http://www.medworm.com/index.php?rid=5095645&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21776604%26dopt%3DAbstract</link>
            <description>Authors: Hodgkinson S, Kaschka WP
    Solute transporters (STs) are an important subgroup of integral membrane proteins that facilitate the translocation of a diverse range of solutes such as sugars, amino acids, and neurotransmitters across cell membranes. Sequence analysis indicates that STs possess multiple stretches of hydrophobic-rich amino acids that are organized into the transmembrane domains (TMDs) of the functional protein, but exactly how the correct spatial arrangement of these domains is achieved remains a challenging problem. We hypothesized that perhaps differences in interdomain hydrophobicity might play some role in this process. To test this hypothesis, we generated a heptadic model of the alpha helix and mapped the average hydrophobicities (coaxial) and hydrophobic momen...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5095645</comments>
            <pubDate>Sun, 31 Jul 2011 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">5095645</guid>        </item>
        <item>
            <title>Svm-based method for protein structural class prediction using secondary structural content and structural information of amino acids.</title>
            <link>http://www.medworm.com/index.php?rid=5095638&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21776605%26dopt%3DAbstract</link>
            <description>Authors: Mohammad TA, Nagarajaram HA
    The knowledge collated from the known protein structures has revealed that the proteins are usually folded into the four structural classes: all-α, all-β, α/β and α + β. A number of methods have been proposed to predict the protein's structural class from its primary structure; however, it has been observed that these methods fail or perform poorly in the cases of distantly related sequences. In this paper, we propose a new method for protein structural class prediction using low homology (twilight-zone) protein sequences dataset. Since protein structural class prediction is a typical classification problem, we have developed a Support Vector Machine (SVM)-based method for protein structural class prediction that uses features derived from the...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5095638</comments>
            <pubDate>Sun, 31 Jul 2011 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">5095638</guid>        </item>
        <item>
            <title>Association of feature gene expression with structural fingerprints of chemical compounds.</title>
            <link>http://www.medworm.com/index.php?rid=5095631&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21776606%26dopt%3DAbstract</link>
            <description>Authors: Li Y, Tu K, Zheng S, Wang J, Li Y, Hao P, Li X
    Exploring the relationship between a chemical structure and its biological function is of great importance for drug discovery. For understanding the mechanisms of drug action, researchers traditionally focused on the molecular structures in the context of interactions with targets. The newly emerged high-throughput &quot;omics&quot; technology opened a new dimension to study the structure-function relationship of chemicals. Previous studies made attempts to introduce transcriptomics data into chemical function investigation. But little effort has been made to link structural fingerprints of compounds with defined intracellular functions, i.e. expression of particular genes and altered pathways. By integrating the chemical structural informa...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5095631</comments>
            <pubDate>Sun, 31 Jul 2011 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">5095631</guid>        </item>
        <item>
            <title>Transfer learning for cytochrome p450 isozyme selectivity prediction.</title>
            <link>http://www.medworm.com/index.php?rid=5095598&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21776607%26dopt%3DAbstract</link>
            <description>Authors: Teramoto R, Kato T
    In the drug discovery process, the metabolic fate of drugs is crucially important to prevent drug-drug interactions. Therefore, P450 isozyme selectivity prediction is an important task for screening drugs of appropriate metabolism profiles. Recently, large-scale activity data of five P450 isozymes (CYP1A2 CYP2C9, CYP3A4, CYP2D6, and CYP2C19) have been obtained using quantitative high-throughput screening with a bioluminescence assay. Although some isozymes share similar selectivities, conventional supervised learning algorithms independently learn a prediction model from each P450 isozyme. They are unable to exploit the other P450 isozyme activity data to improve the predictive performance of each P450 isozyme's selectivity. To address this issue, we apply t...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5095598</comments>
            <pubDate>Sun, 31 Jul 2011 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">5095598</guid>        </item>
        <item>
            <title>A methodology based on molecular interactions and pathways to find candidate genes associated to diseases: its application to schizophrenia and Alzheimer's disease.</title>
            <link>http://www.medworm.com/index.php?rid=5095591&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21776608%26dopt%3DAbstract</link>
            <description>Authors: Ochagavía ME, Miranda J, Nazábal M, Martin A, Novoa LI, Bringas R, Fernández-DE-Cossío J, Camacho H
    Experimental techniques for the identification of genes associated with diseases are expensive and have certain limitations. In this scenario, computational methods are useful tools to identify lists of promising genes for further experimental verification. This paper describes a flexible methodology for the in silico prediction of genes associated with diseases combining the use of available tools for gene enrichment analysis, gene network generation and gene prioritization. A set of reference genes, with a known association to a disease, is used as bait to extract candidate genes from molecular interaction networks and enriched pathways. In a second step, prioritization me...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5095591</comments>
            <pubDate>Sun, 31 Jul 2011 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">5095591</guid>        </item>
        <item>
            <title>Computational challenges of tumor spheroid modeling.</title>
            <link>http://www.medworm.com/index.php?rid=5095530&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21776609%26dopt%3DAbstract</link>
            <description>This study suggests new ways to explore the initial growth phase of solid tumors and to optimize antitumor treatments.
    PMID: 21776609 [PubMed - in process] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5095530</comments>
            <pubDate>Sun, 31 Jul 2011 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">5095530</guid>        </item>
        <item>
            <title>Visualization in simulation tools: requirements and a tool specification to support the teaching of dynamic biological processes.</title>
            <link>http://www.medworm.com/index.php?rid=5095501&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21776610%26dopt%3DAbstract</link>
            <description>Authors: Jørgensen KM, Haddow PC
    Simulation tools are playing an increasingly important role behind advances in the field of systems biology. However, the current generation of biological science students has either little or no experience with such tools. As such, this educational glitch is limiting both the potential use of such tools as well as the potential for tighter cooperation between the designers and users. Although some simulation tool producers encourage their use in teaching, little attempt has hitherto been made to analyze and discuss their suitability as an educational tool for noncomputing science students. In general, today's simulation tools assume that the user has a stronger mathematical and computing background than that which is found in most biological science c...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5095501</comments>
            <pubDate>Sun, 31 Jul 2011 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">5095501</guid>        </item>
        <item>
            <title>Optimal pairwise alignment of fixed protein structures in subquadratic time.</title>
            <link>http://www.medworm.com/index.php?rid=5049729&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21714130%26dopt%3DAbstract</link>
            <description>We present a subquadratic running time algorithm capable of computing an alignment that optimizes one of the most widely used measures of protein structure similarity, defined as the number of pairs of residues in two proteins that can be superimposed under a predefined distance cutoff. The algorithm presented in this article can be used to significantly improve the speed-accuracy tradeoff in a number of popular protein structure alignment methods.
    PMID: 21714130 [PubMed - in process] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5049729</comments>
            <pubDate>Tue, 31 May 2011 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">5049729</guid>        </item>
        <item>
            <title>In search of the protein native state with a probabilistic sampling approach.</title>
            <link>http://www.medworm.com/index.php?rid=5049727&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21714131%26dopt%3DAbstract</link>
            <description>Authors: Olson B, Molloy K, Shehu A
    The three-dimensional structure of a protein is a key determinant of its biological function. Given the cost and time required to acquire this structure through experimental means, computational models are necessary to complement wet-lab efforts. Many computational techniques exist for navigating the high-dimensional protein conformational search space, which is explored for low-energy conformations that comprise a protein's native states. This work proposes two strategies to enhance the sampling of conformations near the native state. An enhanced fragment library with greater structural diversity is used to expand the search space in the context of fragment-based assembly. To manage the increased complexity of the search space, only a representative...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5049727</comments>
            <pubDate>Tue, 31 May 2011 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">5049727</guid>        </item>
        <item>
            <title>A two-stage evolutionary approach for effective classification of hypersensitive DNA sequences.</title>
            <link>http://www.medworm.com/index.php?rid=5049725&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21714132%26dopt%3DAbstract</link>
            <description>Authors: Kamath U, Shehu A, DE Jong KA
    Hypersensitive (HS) sites in genomic sequences are reliable markers of DNA regulatory regions that control gene expression. Annotation of regulatory regions is important in understanding phenotypical differences among cells and diseases linked to pathologies in protein expression. Several computational techniques are devoted to mapping out regulatory regions in DNA by initially identifying HS sequences. Statistical learning techniques like Support Vector Machines (SVM), for instance, are employed to classify DNA sequences as HS or non-HS. This paper proposes a method to automate the basic steps in designing an SVM that improves the accuracy of such classification. The method proceeds in two stages and makes use of evolutionary algorithms. An evolu...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5049725</comments>
            <pubDate>Tue, 31 May 2011 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">5049725</guid>        </item>
        <item>
            <title>Ranking valid topologies of the secondary structure elements using a constraint graph.</title>
            <link>http://www.medworm.com/index.php?rid=5049723&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21714133%26dopt%3DAbstract</link>
            <description>Authors: Al Nasr K, Ranjan D, Zubair M, He J
    Electron cryo-microscopy is a fast advancing biophysical technique to derive three-dimensional structures of large protein complexes. Using this technique, many density maps have been generated at intermediate resolution such as 6-10 Å resolution. Although it is challenging to derive the backbone of the protein directly from such density maps, secondary structure elements such as helices and β-sheets can be computationally detected. Our work in this paper provides an approach to enumerate the top-ranked possible topologies instead of enumerating the entire population of the topologies. This approach is particularly practical for large proteins. We developed a directed weighted graph, the topology graph, to represent the secondary structure...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5049723</comments>
            <pubDate>Tue, 31 May 2011 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">5049723</guid>        </item>
        <item>
            <title>A method for the detection of meaningful and reproducible group signatures from gene expression profiles.</title>
            <link>http://www.medworm.com/index.php?rid=5049718&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21714134%26dopt%3DAbstract</link>
            <description>Authors: Licamele L, Getoor L
    Gene expression microarrays are commonly used to detect the biological signature of a disease or to gain a better understanding of the underlying mechanism of how a group of drugs treat a specific disease. The outcome of such experiments, e.g. the signature, is a list of differentially expressed genes. Reproducibility across independent experiments remains a challenge. We are interested in creating a method that can detect the shared signature of a group of expression profiles, e.g. a group of samples from individuals with the same disease or a group of drugs that treat the same therapeutic indication. We have developed a novel Weighted Influence - Rank of Ranks (WIMRR) method, and we demonstrate its ability to produce both meaningful and reproducible grou...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5049718</comments>
            <pubDate>Tue, 31 May 2011 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">5049718</guid>        </item>
        <item>
            <title>Optimization of therapeutic proteins to delete T-cell epitopes while maintaining beneficial residue interactions.</title>
            <link>http://www.medworm.com/index.php?rid=4802593&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21523929%26dopt%3DAbstract</link>
            <description>Authors: Parker AS, Griswold KE, Bailey-Kellogg C
    Exogenous enzymes, signaling peptides, and other classes of nonhuman proteins represent a potentially massive but largely untapped pool of biotherapeutic agents. Adapting a foreign protein for therapeutic use poses numerous design challenges. We focus here on one significant problem: modifying the protein to mitigate the immune response mounted against &quot;non-self&quot; proteins, while not adversely affecting the protein's stability or therapeutic activity. In order to propose such variants suitable for experimental evaluation, this paper develops a computational method to select sets of mutations predicted to delete immunogenic T-cell epitopes, as evaluated by a 9-mer potential, while simultaneously maintaining important residues and residue ...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4802593</comments>
            <pubDate>Thu, 31 Mar 2011 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">4802593</guid>        </item>
        <item>
            <title>Temporal graphical models for cross-species gene regulatory network discovery.</title>
            <link>http://www.medworm.com/index.php?rid=4802592&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21523930%26dopt%3DAbstract</link>
            <description>Authors: Liu Y, Niculescu-Mizil A, Lozano A, Lu Y
    Many genes and biological processes function in similar ways across different species. Cross-species gene expression analysis, as a powerful tool to characterize the dynamical properties of the cell, has found a number of applications, such as identifying a conserved core set of cell cycle genes. However, to the best of our knowledge, there is limited effort on developing appropriate techniques to capture the causality relations between genes from time-series microarray data across species. In this paper, we present hidden Markov random field regression with L(1) penalty to uncover the regulatory network structure for different species. The algorithm provides a framework for sharing information across species via hidden component graphs...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4802592</comments>
            <pubDate>Thu, 31 Mar 2011 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">4802592</guid>        </item>
        <item>
            <title>Classification of large microarray datasets using fast random forest construction.</title>
            <link>http://www.medworm.com/index.php?rid=4802591&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21523931%26dopt%3DAbstract</link>
            <description>CLASSIFICATION OF LARGE MICROARRAY DATASETS USING FAST RANDOM FOREST CONSTRUCTION.
    J Bioinform Comput Biol. 2011 Apr;9(2):251-267
    Authors: Manilich EA, OzsoyoǦlu ZM, Trubachev V, Radivoyevitch T
    Random forest is an ensemble classification algorithm. It performs well when most predictive variables are noisy and can be used when the number of variables is much larger than the number of observations. The use of bootstrap samples and restricted subsets of attributes makes it more powerful than simple ensembles of trees. The main advantage of a random forest classifier is its explanatory power: it measures variable importance or impact of each factor on a predicted class label. These characteristics make the algorithm ideal for microarray data. It was shown to build models with hig...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4802591</comments>
            <pubDate>Thu, 31 Mar 2011 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">4802591</guid>        </item>
        <item>
            <title>COMPARING MULTIPLE ChIP-SEQUENCING EXPERIMENTS.</title>
            <link>http://www.medworm.com/index.php?rid=4802590&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21523932%26dopt%3DAbstract</link>
            <description>In this study, we present a method that can effectively select differential regions of the genome based on protein-binding profiles over multiple experiments using real data points without any normalization among the samples.
    PMID: 21523932 [PubMed - in process] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4802590</comments>
            <pubDate>Thu, 31 Mar 2011 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">4802590</guid>        </item>
        <item>
            <title>Analyzing modular RNA structure reveals low global structural entropy in microrna sequence.</title>
            <link>http://www.medworm.com/index.php?rid=4802589&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21523933%26dopt%3DAbstract</link>
            <description>Authors: Shaw TI, Manzour A, Wang Y, Malmberg RL, Cai L
    Secondary structure remains the most exploitable feature for noncoding RNA (ncRNA) gene finding in genomes. However, methods based on secondary structure prediction may generate superfluous amount of candidates for validation and have yet to deliver the desired performance that can complement experimental efforts in ncRNA gene finding. This paper investigates a novel method, unpaired structural entropy (USE) as a measurement for the structure fold stability of ncRNAs. USE proves to be effective in identifying from the genome background a class of ncRNAs, such as precursor microRNAs (pre-miRNAs) that contains a long stem hairpin loop. USE correlates well and performs better than other measures on pre-miRNAs, including the previousl...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4802589</comments>
            <pubDate>Thu, 31 Mar 2011 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">4802589</guid>        </item>
        <item>
            <title>Lex-svm: exploring the potential of exon expression profiling for disease classification.</title>
            <link>http://www.medworm.com/index.php?rid=4802588&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21523934%26dopt%3DAbstract</link>
            <description>Authors: Yuan X, Zhao Y, Liu C, Bu D
    Exon expression profiling technologies, including exon arrays and RNA-Seq, measure the abundance of every exon in a gene. Compared with gene expression profiling technologies like 3' array, exon expression profiling technologies could detect alterations in both transcription and alternative splicing, therefore they are expected to be more sensitive in diagnosis. However, exon expression profiling also brings higher dimension, more redundancy, and significant correlation among features. Ignoring the correlation structure among exons of a gene, a popular classification method like L1-SVM selects exons individually from each gene and thus is vulnerable to noise. To overcome this limitation, we present in this paper a new variant of SVM named Lex-SVM to...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4802588</comments>
            <pubDate>Thu, 31 Mar 2011 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">4802588</guid>        </item>
        <item>
            <title>ncRNA CONSENSUS SECONDARY STRUCTURE DERIVATION USING GRAMMAR STRINGS.</title>
            <link>http://www.medworm.com/index.php?rid=4802587&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21523935%26dopt%3DAbstract</link>
            <description>Authors: Achawanantakun R, Sun Y, Takyar SS
    Many noncoding RNAs (ncRNAs) function through both their sequences and secondary structures. Thus, secondary structure derivation is an important issue in today's RNA research. The state-of-the-art structure annotation tools are based on comparative analysis, which derives consensus structure of homologous ncRNAs. Despite promising results from existing ncRNA aligning and consensus structure derivation tools, there is a need for more efficient and accurate ncRNA secondary structure modeling and alignment methods. In this work, we introduce a consensus structure derivation approach based on grammar string, a novel ncRNA secondary structure representation that encodes an ncRNA's sequence and secondary structure in the parameter space of a conte...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4802587</comments>
            <pubDate>Thu, 31 Mar 2011 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">4802587</guid>        </item>
        <item>
            <title>Inferring haplotypes from genotypes on a pedigree with mutations, genotyping errors and missing alleles.</title>
            <link>http://www.medworm.com/index.php?rid=4802586&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21523936%26dopt%3DAbstract</link>
            <description>Authors: Wang WB, Jiang T
    Inferring the haplotypes of the members of a pedigree from their genotypes has been extensively studied. However, most studies do not consider genotyping errors and de novo mutations. In this paper, we study how to infer haplotypes from genotype data that may contain genotyping errors, de novo mutations, and missing alleles. We assume that there are no recombinants in the genotype data, which is usually true for tightly linked markers. We introduce a combinatorial optimization problem, called haplotype configuration with mutations and errors (HCME), which calls for haplotype configurations consistent with the given genotypes that incur no recombinants and require the minimum number of mutations and errors. HCME is NP-hard. To solve the problem, we propose a he...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4802586</comments>
            <pubDate>Thu, 31 Mar 2011 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">4802586</guid>        </item>
        <item>
            <title>RECENT advances on structural bioinformatics, cell motion simulation, functional module identification, copy number variation, and protease substrate prediction and some critical comments on HMMER2.</title>
            <link>http://www.medworm.com/index.php?rid=4637762&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21417095%26dopt%3DAbstract</link>
            <description>Authors: Wong L
    
    PMID: 21417095 [PubMed - in process] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4637762</comments>
            <pubDate>Tue, 01 Feb 2011 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4637762</guid>        </item>
        <item>
            <title>Predicting protein folding rate from amino Acid sequence.</title>
            <link>http://www.medworm.com/index.php?rid=4524808&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21328704%26dopt%3DAbstract</link>
            <description>Authors: Guo J, Rao N
    Predicting protein folding rate from amino acid sequence is an important challenge in computational and molecular biology. Over the past few years, many methods have been developed to reflect the correlation between the folding rates and protein structures and sequences. In this paper, we present an effective method, a combined neural network - genetic algorithm approach, to predict protein folding rates only from amino acid sequences, without any explicit structural information. The originality of this paper is that, for the first time, it tackles the effect of sequence order. The proposed method provides a good correlation between the predicted and experimental folding rates. The correlation coefficient is 0.80 and the standard error is 2.65 for 93 proteins, the...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4524808</comments>
            <pubDate>Tue, 01 Feb 2011 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4524808</guid>        </item>
        <item>
            <title>Error tolerant NMR backbone resonance assignment and automated structure generation.</title>
            <link>http://www.medworm.com/index.php?rid=4524807&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21328705%26dopt%3DAbstract</link>
            <description>Authors: Alipanahi B, Gao X, Karakoc E, Li SC, Balbach F, Feng G, Donaldson L, Li M
    Error tolerant backbone resonance assignment is the cornerstone of the NMR structure determination process. Although a variety of assignment approaches have been developed, none works sufficiently well on noisy fully automatically picked peaks to enable the subsequent automatic structure determination steps. We have designed an integer linear programming (ILP) based assignment system (IPASS) that has enabled fully automatic protein structure determination for four test proteins. IPASS employs probabilistic spin system typing based on chemical shifts and secondary structure predictions. Furthermore, IPASS extracts connectivity information from the inter-residue information and the (automatically picked) ...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4524807</comments>
            <pubDate>Tue, 01 Feb 2011 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4524807</guid>        </item>
        <item>
            <title>Prediction of the exposure status of transmembrane Beta barrel residues from protein sequence.</title>
            <link>http://www.medworm.com/index.php?rid=4524806&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21328706%26dopt%3DAbstract</link>
            <description>We present BTMX (Beta barrel TransMembrane eXposure), a computational method to predict the exposure status (i.e. exposed to the bilayer or hidden in the protein structure) of transmembrane residues in transmembrane beta barrel proteins (TMBs). BTMX predicts the exposure status of known TM residues with an accuracy of 84.2% over 2,225 residues and provides a confidence score for all predictions. Predictions made are in concert with the fact that hydrophobic residues tend to be more exposed to the bilayer. The biological relevance of the input parameters is also discussed. The highest prediction accuracy is obtained when a sliding window comprising three residues with similar C(α) - C(β) vector orientations is employed. The prediction accuracy of the BTMX method on a separate unseen non-r...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4524806</comments>
            <pubDate>Tue, 01 Feb 2011 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4524806</guid>        </item>
        <item>
            <title>Improved sequence-based prediction of strand residues.</title>
            <link>http://www.medworm.com/index.php?rid=4524805&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21328707%26dopt%3DAbstract</link>
            <description>Authors: Kedarisetti KD, Mizianty MJ, Dick S, Kurgan L
    Accurate identification of strand residues aids prediction and analysis of numerous structural and functional aspects of proteins. We propose a sequence-based predictor, BETArPRED, which improves prediction of strand residues and β-strand segments. BETArPRED uses a novel design that accepts strand residues predicted by SSpro and predicts the remaining positions utilizing a logistic regression classifier with nine custom-designed features. These are derived from the primary sequence, the secondary structure (SS) predicted by SSpro, PSIPRED and SPINE, and residue depth as predicted by RDpred. Our features utilize certain local (window-based) patterns in the predicted SS and combine information about the predicted SS and residue dept...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4524805</comments>
            <pubDate>Tue, 01 Feb 2011 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4524805</guid>        </item>
        <item>
            <title>Simulation of cell movement and interaction.</title>
            <link>http://www.medworm.com/index.php?rid=4524804&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21328708%26dopt%3DAbstract</link>
            <description>Authors: Taylor W, Katsimitsoulia Z, Poliakov A
    A mechanical model of cell motion was developed that reproduced the behaviour of cells in 2-dimensional culture. Cell adhesion was modelled with inter-cellular cross-links that attached for different times giving a range of adhesion strength. Simulations revealed an adhesion threshold below which cell motion was almost unaffected and above which cells moved as if permanently linked. Comparing simulated cell clusters (with known connections) to calculated clusters (based only on distance) showed that the calculated clusters did not correspond well across the full size range from small to big clusters. The radial distribution function of the cells was found to be a better measure, giving a good correlation with the known cell linkage throug...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4524804</comments>
            <pubDate>Tue, 01 Feb 2011 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4524804</guid>        </item>
        <item>
            <title>Enhancing biological relevance of a weighted gene co-expression network for functional module identification.</title>
            <link>http://www.medworm.com/index.php?rid=4524803&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21328709%26dopt%3DAbstract</link>
            <description>Authors: Prom-On S, Chanthaphan A, Chan JH, Meechai A
    Relationships among gene expression levels may be associated with the mechanisms of the disease. While identifying a direct association such as a difference in expression levels between case and control groups links genes to disease mechanisms, uncovering an indirect association in the form of a network structure may help reveal the underlying functional module associated with the disease under scrutiny. This paper presents a method to improve the biological relevance in functional module identification from the gene expression microarray data by enhancing the structure of a weighted gene co-expression network using minimum spanning tree. The enhanced network, which is called a backbone network, contains only the essential structura...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4524803</comments>
            <pubDate>Tue, 01 Feb 2011 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4524803</guid>        </item>
        <item>
            <title>A novel approach to DNA copy number data segmentation.</title>
            <link>http://www.medworm.com/index.php?rid=4524802&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21328710%26dopt%3DAbstract</link>
            <description>Authors: Wang S, Wang Y, Xie Y, Xiao G
    DNA copy number (DCN) is the number of copies of DNA at a region of a genome. The alterations of DCN are highly associated with the development of different tumors. Recently, microarray technologies are being employed to detect DCN changes at many loci at the same time in tumor samples. The resulting DCN data are often very noisy, and the tumor sample is often contaminated by normal cells. The goal of computational analysis of array-based DCN data is to infer the underlying DCNs from raw DCN data. Previous methods for this task do not model the tumor/normal cell mixture ratio explicitly and they cannot output segments with DCN annotations. We developed a novel model-based method using the minimum description length (MDL) principle for DCN data seg...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4524802</comments>
            <pubDate>Tue, 01 Feb 2011 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4524802</guid>        </item>
        <item>
            <title>Bioinformatic approaches for predicting substrates of proteases.</title>
            <link>http://www.medworm.com/index.php?rid=4524801&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21328711%26dopt%3DAbstract</link>
            <description>Authors: Song J, Tan H, Boyd SE, Shen H, Mahmood K, Webb GI, Akutsu T, Whisstock JC, Pike RN
    Proteases have central roles in &quot;life and death&quot; processes due to their important ability to catalytically hydrolyze protein substrates, usually altering the function and/or activity of the target in the process. Knowledge of the substrate specificity of a protease should, in theory, dramatically improve the ability to predict target protein substrates. However, experimental identification and characterization of protease substrates is often difficult and time-consuming. Thus solving the &quot;substrate identification&quot; problem is fundamental to both understanding protease biology and the development of therapeutics that target specific protease-regulated pathways. In this context, bioinformatic pred...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4524801</comments>
            <pubDate>Tue, 01 Feb 2011 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4524801</guid>        </item>
        <item>
            <title>The janus-faced e-values of hmmer2: extreme value distribution or logistic function?</title>
            <link>http://www.medworm.com/index.php?rid=4524800&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21328712%26dopt%3DAbstract</link>
            <description>Authors: Wong WC, Maurer-Stroh S, Eisenhaber F
    E-value guided extrapolation of protein domain annotation from libraries such as Pfam with the HMMER suite is indispensable for hypothesizing about the function of experimentally uncharacterized protein sequences. Since the recent release of HMMER3 does not supersede all functions of HMMER2, the latter will remain relevant for ongoing research as well as for the evaluation of annotations that reside in databases and in the literature. In HMMER2, the E-value is computed from the score via a logistic function or via a domain model-specific extreme value distribution (EVD); the lower of the two is returned as E-value for the domain hit in the query sequence. We find that, for thousands of domain models, this treatment results in switching fro...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4524800</comments>
            <pubDate>Tue, 01 Feb 2011 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4524800</guid>        </item>
        <item>
            <title>Advances in genome informatics.</title>
            <link>http://www.medworm.com/index.php?rid=4274376&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21155015%26dopt%3DAbstract</link>
            <description>ADVANCES IN GENOME INFORMATICS.
    J Bioinform Comput Biol. 2010 Dec;8(supp01):v-viii
    Authors: Zhao XM, Li Y, Li M, Chen L
    No abstract received.
    PMID: 21155015 [PubMed - as supplied by publisher] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4274376</comments>
            <pubDate>Wed, 01 Dec 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4274376</guid>        </item>
        <item>
            <title>Functional classification of protein 3d structures from predicted local interaction sites.</title>
            <link>http://www.medworm.com/index.php?rid=4274375&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21155016%26dopt%3DAbstract</link>
            <description>FUNCTIONAL CLASSIFICATION OF PROTEIN 3D STRUCTURES FROM PREDICTED LOCAL INTERACTION SITES.
    J Bioinform Comput Biol. 2010 Dec;8(supp01):1-15
    Authors: Parasuram R, Lee JS, Yin P, Somarowthu S, Ondrechen MJ
    A new approach to the functional classification of protein 3D structures is described with application to some examples from structural genomics. This approach is based on functional site prediction with THEMATICS and POOL. THEMATICS employs calculated electrostatic potentials of the query structure. POOL is a machine learning method that utilizes THEMATICS features and has been shown to predict accurate, precise, highly localized interaction sites. Extension to the functional classification of structural genomics proteins is now described. Predicted functionally important resi...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4274375</comments>
            <pubDate>Wed, 01 Dec 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4274375</guid>        </item>
        <item>
            <title>BiMFG: BIOINFORMATICS TOOLS FOR MARINE AND FRESHWATER SPECIES.</title>
            <link>http://www.medworm.com/index.php?rid=4274374&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21155017%26dopt%3DAbstract</link>
            <description>Authors: Shih TH, Chen CM, Wang HW, Pai TW, Chang HT
    Biomolecule sequences and structures of land, air and water species are determined rapidly and the data entries are unevenly distributed for different organisms. It frequently leads to the BLAST results of homologous search containing undesirable entries from organisms living in different environments. To reduce irrelevant searching results, a separate database for comparative genomics is urgently required. A comprehensive bioinformatics tool set and an integrated database, named Bioinformatics tools for Marine and Freshwater Genomics (BiMFG), are constructed for comparative analyses among model species and underwater species. Novel matching techniques based on conserved motifs and/or secondary structure elements are designed for eff...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4274374</comments>
            <pubDate>Wed, 01 Dec 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4274374</guid>        </item>
        <item>
            <title>Stepwise origin and functional diversification of the afl subfamily b3 genes during land plant evolution.</title>
            <link>http://www.medworm.com/index.php?rid=4274373&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21155018%26dopt%3DAbstract</link>
            <description>STEPWISE ORIGIN AND FUNCTIONAL DIVERSIFICATION OF THE AFL SUBFAMILY B3 GENES DURING LAND PLANT EVOLUTION.
    J Bioinform Comput Biol. 2010 Dec;8(supp01):33-45
    Authors: Li Y, Jin K, Zhu Z, Yang J
    The AFL genes (ABI3/VP1, FUS3 and LEC2) belong to the plant-specific B3 superfamily, playing important roles in regulating seed development and maturation. It is unclear, however, whether these genes appeared at the same time as the origin of seed plants and if all these genes are necessary and sufficient for seed development for all seed plants. By conducting a genome-wide comparative analysis of the putative AFL genes in various plant species, we found that the ABI3 homologous genes existed in all land plant genomes, but the FUS3 homologous were present only in seed plant genomes and the...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4274373</comments>
            <pubDate>Wed, 01 Dec 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4274373</guid>        </item>
        <item>
            <title>A method based on local density and random walks for complexes detection in protein interaction networks.</title>
            <link>http://www.medworm.com/index.php?rid=4274372&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21155019%26dopt%3DAbstract</link>
            <description>A METHOD BASED ON LOCAL DENSITY AND RANDOM WALKS FOR COMPLEXES DETECTION IN PROTEIN INTERACTION NETWORKS.
    J Bioinform Comput Biol. 2010 Dec;8(supp01):47-62
    Authors: Yu L, Gao L, Li K
    In this paper, we present a method based on local density and random walks (LDRW) for core-attachment complexes detection in protein-protein interaction (PPI) networks whether they are weighted or not. Our LDRW method consists of two stages. Firstly, it finds all the protein-complex cores based on local density of subnetwork. Then it uses random walks with restarts for finding the attachment proteins of each detected core to form complexes. We evaluate the effectiveness of our method using two different yeast PPI networks and validate the biological significance of the predicted protein complexes u...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4274372</comments>
            <pubDate>Wed, 01 Dec 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4274372</guid>        </item>
        <item>
            <title>Compound analysis via graph kernels incorporating chirality.</title>
            <link>http://www.medworm.com/index.php?rid=4274371&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21155020%26dopt%3DAbstract</link>
            <description>COMPOUND ANALYSIS VIA GRAPH KERNELS INCORPORATING CHIRALITY.
    J Bioinform Comput Biol. 2010 Dec;8(supp01):63-81
    Authors: Brown JB, Urata T, Tamura T, Arai MA, Kawabata T, Akutsu T
    High accuracy is paramount when predicting biochemical characteristics using Quantitative Structural-Property Relationships (QSPRs). Although existing graph-theoretic kernel methods combined with machine learning techniques are efficient for QSPR model construction, they cannot distinguish topologically identical chiral compounds which often exhibit different biological characteristics. In this paper, we propose a new method that extends the recently developed tree pattern graph kernel to accommodate stereoisomers. We show that Support Vector Regression (SVR) with a chiral graph kernel is useful for ta...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4274371</comments>
            <pubDate>Wed, 01 Dec 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4274371</guid>        </item>
        <item>
            <title>Environmental dependency of gene knockouts on phenotype microarray analysis in escherichia coli.</title>
            <link>http://www.medworm.com/index.php?rid=4274370&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21155021%26dopt%3DAbstract</link>
            <description>ENVIRONMENTAL DEPENDENCY OF GENE KNOCKOUTS ON PHENOTYPE MICROARRAY ANALYSIS IN ESCHERICHIA COLI.
    J Bioinform Comput Biol. 2010 Dec;8(supp01):83-99
    Authors: Tohsato Y, Baba T, Mazaki Y, Ito M, Wanner BL, Mori H
    Systematic studies have revealed that single gene deletions often display little phenotypic effects under laboratory conditions and that in many cases gene dispensability depends on the experimental conditions. To elucidate the environmental dependency of genes, we analyzed the effects of gene deletions by Phenotype MicroArray™ (PM), a system for quantitative screening of thousands of phenotypes in a high-throughput manner. Here, we proposed a new statistical approach to minimize error inherent in measurements of low respiration rates and find which mutants showed signi...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4274370</comments>
            <pubDate>Wed, 01 Dec 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4274370</guid>        </item>
        <item>
            <title>G6PD-MutDB: A MUTATION AND PHENOTYPE DATABASE OF GLUCOSE-6-PHOSPHATE (G6PD) DEFICIENCY.</title>
            <link>http://www.medworm.com/index.php?rid=4274369&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21155022%26dopt%3DAbstract</link>
            <description>Authors: Zhao X, Li Z, Zhang X
    Glucose-6-phosphate dehydrogenase (G6PD) deficiency is the most common hereditary enzymatic disorder of red blood cells in humans due to mutations in the G6PD gene. The G6PD enzyme catalyzes the first step in the pentose phosphate pathway to protect cells against oxidative stress. Mutations in the G6PD gene will cause functional variants with various biochemical and clinical phenotypes. So far, about 160 mutations along with more than 400 biochemical variants have been described. G6PD-MutDB is a disease-specific resource of G6PD deficiency, collecting and integrating G6PD mutations with biochemical and clinical phenotypes. Data of G6PD deficiency is manually extracted from published papers, focusing primarily on variants with identified mutation and well-...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4274369</comments>
            <pubDate>Wed, 01 Dec 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4274369</guid>        </item>
        <item>
            <title>Racial differences in mlh1 and msh2 mutation: an analysis of yellow race and white race based on the insight database.</title>
            <link>http://www.medworm.com/index.php?rid=4274368&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21155023%26dopt%3DAbstract</link>
            <description>RACIAL DIFFERENCES IN MLH1 AND MSH2 MUTATION: AN ANALYSIS OF YELLOW RACE AND WHITE RACE BASED ON THE INSIGHT DATABASE.
    J Bioinform Comput Biol. 2010 Dec;8(supp01):111-125
    Authors: Wei W, Liu L, Chen J, Jin K, Jiang F, Liu F, Fan R, Cheng Z, Shen M, Xue C, Cai S, Xu Y, Nan P
    MLH1 and MSH2 mutations underlie 90% of hereditary nonpolyposis colorectal cancer (HNPCC) mutations. The International Society of Gastrointestinal Hereditary Tumors (InSiGHT) has established an international database of mutations associated with HNPCC. Based on the InSiGHT database and the original references that reported the mutations, we analyzed the distributions of MLH1 and MSH2 mutations in yellow race and white race respectively and compared them subsequently. We found: (1) the distributions of mutati...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4274368</comments>
            <pubDate>Wed, 01 Dec 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4274368</guid>        </item>
        <item>
            <title>Efficient mining of haplotype patterns for linkage disequilibrium mapping.</title>
            <link>http://www.medworm.com/index.php?rid=4274367&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21155024%26dopt%3DAbstract</link>
            <description>EFFICIENT MINING OF HAPLOTYPE PATTERNS FOR LINKAGE DISEQUILIBRIUM MAPPING.
    J Bioinform Comput Biol. 2010 Dec;8(supp01):127-146
    Authors: Lin L, Wong L, Leong TY, Lai PS
    Effective identification of disease-causing gene locations can have significant impact on patient management decisions that will ultimately increase survival rates and improve the overall quality of health care. Linkage disequilibrium mapping is the process of finding disease gene locations through comparisons of haplotype frequencies between disease chromosomes and normal chromosomes. This work presents a new method for linkage disequilibrium mapping. The main advantage of the proposed algorithm, called LinkageTracker, is its consistency in producing good predictive accuracy under different conditions, including...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4274367</comments>
            <pubDate>Wed, 01 Dec 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4274367</guid>        </item>
        <item>
            <title>Cancer classification from the gene expression profiles by discriminant kernel-pls.</title>
            <link>http://www.medworm.com/index.php?rid=4274366&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21155025%26dopt%3DAbstract</link>
            <description>CANCER CLASSIFICATION FROM THE GENE EXPRESSION PROFILES BY DISCRIMINANT KERNEL-PLS.
    J Bioinform Comput Biol. 2010 Dec;8(supp01):147-160
    Authors: Tang KL, Yao WJ, Li TH, Li YX, Cao ZW
    Cancer diagnosis depending on microarray technology has drawn more and more attention in the past few years. Accurate and fast diagnosis results make gene expression profiling produced from microarray widely used by a large range of researchers. Much research work highlights the importance of gene selection and gains good results. However, the minimum sets of genes derived from different methods are seldom overlapping and often inconsistent even for the same set of data, partially because of the complexity of cancer disease. In this paper, cancer classification was attempted in an alternative way o...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4274366</comments>
            <pubDate>Wed, 01 Dec 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4274366</guid>        </item>
        <item>
            <title>Digout: viewing differential expression genes as outliers.</title>
            <link>http://www.medworm.com/index.php?rid=4274365&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21155026%26dopt%3DAbstract</link>
            <description>In conclusion, a multivariate outlier analysis algorithm, like DigOut, is particularly useful for selecting DE genes from non-replicated multi-conditional gene expression dataset.
    PMID: 21155026 [PubMed - as supplied by publisher] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4274365</comments>
            <pubDate>Wed, 01 Dec 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4274365</guid>        </item>
        <item>
            <title>Isoform abundance inference provides a more accurate estimation of gene expression levels in rna-seq.</title>
            <link>http://www.medworm.com/index.php?rid=4274364&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21155027%26dopt%3DAbstract</link>
            <description>ISOFORM ABUNDANCE INFERENCE PROVIDES A MORE ACCURATE ESTIMATION OF GENE EXPRESSION LEVELS IN RNA-SEQ.
    J Bioinform Comput Biol. 2010 Dec;8(supp01):177-192
    Authors: Wang X, Wu Z, Zhang X
    Due to its unprecedented high-resolution and detailed information, RNA-seq technology based on next-generation high-throughput sequencing significantly boosts the ability to study transcriptomes. The estimation of genes' transcript abundance levels or gene expression levels has always been an important question in research on the transcriptional regulation and gene functions. On the basis of the concept of Reads Per Kilo-base per Million reads (RPKM), taking the union-intersection genes (UI-based) and summing up inferred isoform abundance (isoform-based) are the two current strategies to estimate...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4274364</comments>
            <pubDate>Wed, 01 Dec 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4274364</guid>        </item>
        <item>
            <title>Identification of functional modules in a ppi network by bounded diameter clustering.</title>
            <link>http://www.medworm.com/index.php?rid=4250228&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21121019%26dopt%3DAbstract</link>
            <description>Authors: Sohaee N, Forst CV
    Dense subgraphs of Protein-Protein Interaction (PPI) graphs are assumed to be potential functional modules and play an important role in inferring the functional behavior of proteins. Increasing amount of available PPI data implies a fast, accurate approach of biological complex identification. Therefore, there are different models and algorithms in identifying functional modules. This paper describes a new graph theoretic clustering algorithm that detects densely connected regions in a large PPI graph. The method is based on finding bounded diameter subgraphs around a seed node. The algorithm has the advantage of being very simple and efficient when compared with other graph clustering methods. This algorithm is tested on the yeast PPI graph and the results...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4250228</comments>
            <pubDate>Wed, 01 Dec 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4250228</guid>        </item>
        <item>
            <title>Multi-factorial analysis of class prediction error: estimating optimal number of biomarkers for various classification rules.</title>
            <link>http://www.medworm.com/index.php?rid=4250227&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21121020%26dopt%3DAbstract</link>
            <description>Authors: Khondoker MR, Bachmann TT, Mewissen M, Dickinson P, Dobrzelecki B, Campbell CJ, Mount AR, Walton AJ, Crain J, Schulze H, Giraud G, Ross AJ, Ciani I, Ember SW, Tlili C, Terry JG, Grant E, McDonnell N, Ghazal P
    Machine learning and statistical model based classifiers have increasingly been used with more complex and high dimensional biological data obtained from high-throughput technologies. Understanding the impact of various factors associated with large and complex microarray datasets on the predictive performance of classifiers is computationally intensive, under investigated, yet vital in determining the optimal number of biomarkers for various classification purposes aimed towards improved detection, diagnosis, and therapeutic monitoring of diseases. We investigate the imp...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4250227</comments>
            <pubDate>Wed, 01 Dec 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4250227</guid>        </item>
        <item>
            <title>On comparing two structured RNA multiple alignments.</title>
            <link>http://www.medworm.com/index.php?rid=4250226&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21121021%26dopt%3DAbstract</link>
            <description>We present a method, called BlockMatch, for aligning two blocks, where a block is an RNA multiple sequence alignment with the consensus secondary structure of the alignment in Stockholm format. The method employs a quadratic-time dynamic programming algorithm for aligning columns and column pairs of the multiple alignments in the blocks. Unlike many other tools that can perform pairwise alignment of either single sequences or structures only, BlockMatch takes into account the characteristics of all the sequences in the blocks along with their consensus structures during the alignment process, thus being able to achieve a high-quality alignment result. We apply BlockMatch to phylogeny reconstruction on a set of 5S rRNA sequences taken from fifteen bacteria species. Experimental results show...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4250226</comments>
            <pubDate>Wed, 01 Dec 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4250226</guid>        </item>
        <item>
            <title>Adepts: advanced Peptide de novo sequencing with a pair of tandem mass spectra.</title>
            <link>http://www.medworm.com/index.php?rid=4250225&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21121022%26dopt%3DAbstract</link>
            <description>Authors: He L, Ma B
    De novo sequencing is an important task in proteomics to identify novel peptide sequences. Traditionally, only one MS/MS spectrum is used for the sequencing of a peptide; however, the use of multiple spectra of the same peptide with different types of fragmentation has the potential to significantly increase the accuracy and practicality of de novo sequencing. Research into the use of multiple spectra is in a nascent stage. We propose a general framework to combine the two different types of MS/MS data. Experiments demonstrate that our method significantly improves the de novo sequencing of existing software.
    PMID: 21121022 [PubMed - in process] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4250225</comments>
            <pubDate>Wed, 01 Dec 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4250225</guid>        </item>
        <item>
            <title>Short prokaryotic DNA fragment binning using a hierarchical classifier based on linear discriminant analysis and principal component analysis.</title>
            <link>http://www.medworm.com/index.php?rid=4250224&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21121023%26dopt%3DAbstract</link>
            <description>Authors: Zheng H, Wu H
    Metagenomics is an emerging field in which the power of genomic analysis is applied to an entire microbial community, bypassing the need to isolate and culture individual microbial species. Assembling of metagenomic DNA fragments is very much like the overlap-layout-consensus procedure for assembling isolated genomes, but is augmented by an additional binning step to differentiate scaffolds, contigs and unassembled reads into various taxonomic groups. In this paper, we employed n-mer oligonucleotide frequencies as the features and developed a hierarchical classifier (PCAHIER) for binning short (≤ 1,000 bps) metagenomic fragments. The principal component analysis was used to reduce the high dimensionality of the feature space. The hierarchical classifier consist...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4250224</comments>
            <pubDate>Wed, 01 Dec 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4250224</guid>        </item>
        <item>
            <title>Bioinformatic analysis of the neutrality of RNA secondary structure elements across genotypes reveals evidence for direct evolution of genetic robustness in HCV.</title>
            <link>http://www.medworm.com/index.php?rid=4250223&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21121024%26dopt%3DAbstract</link>
            <description>This study provides supporting evidence for direct evolution of genetic robustness that is not limited to noncoding RNAs participating in gene regulation, but includes functionally important structural elements of the hepatitis C virus (HCV) that show excess of robustness beyond the intrinsic robustness of their stem-loop structure. These findings further support the adaptive behavior of genetic robustness in functional RNAs of various types that seem to have evolved with selection pressure towards increased robustness.
    PMID: 21121024 [PubMed - in process] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4250223</comments>
            <pubDate>Wed, 01 Dec 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4250223</guid>        </item>
        <item>
            <title>Quantifying slow evolutionary dynamics in RNA fitness landscapes.</title>
            <link>http://www.medworm.com/index.php?rid=4250222&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21121025%26dopt%3DAbstract</link>
            <description>Authors: Sulc P, Wagner A, Martin OC
    We re-examine the evolutionary dynamics of RNA secondary structures under directional selection towards an optimum RNA structure. We find that the punctuated equilibria lead to a very slow approach to the optimum, following on average an inverse power of the evolutionary time. In addition, our study of the trajectories shows that the out-of-equilibrium effects due to the evolutionary process are very weak. In particular, the distribution of genotypes is close to that arising during equilibrium stabilizing selection. As a consequence, the evolutionary dynamics leave almost no measurable out-of-equilibrium trace, only the transition genotypes (close to the border between different periods of stasis) have atypical mutational properties.
    PMID: 21121...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4250222</comments>
            <pubDate>Wed, 01 Dec 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4250222</guid>        </item>
        <item>
            <title>Dynamic equilibrium of reconstituting hematopoietic stem cell populations.</title>
            <link>http://www.medworm.com/index.php?rid=4250221&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21121026%26dopt%3DAbstract</link>
            <description>We describe the difficulties here and identify ready solutions which only require appropriate use of variance-stabilizing transformations. From these we obtain estimators for the steady state, or dynamic equilibrium, of the number of hematopoietic stem cells involved in repopulating the marrow. The calculations themselves are not too involved. We give the distribution theory for the estimator as well as simple approximations for practical application. As an illustration, we rework on data recently gathered to address the question as to whether or not reconstitution of marrow grafts in the clinical setting might be considered to be oligoclonal.
    PMID: 21121026 [PubMed - in process] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4250221</comments>
            <pubDate>Wed, 01 Dec 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4250221</guid>        </item>
        <item>
            <title>New results in biological sequence analysis, complex gene–disease association, qPCR calculation, and biological text mining.</title>
            <link>http://www.medworm.com/index.php?rid=4138916&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D21046831%26dopt%3DAbstract</link>
            <description>Authors: Wong L
    
    PMID: 21046831 [PubMed - in process] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4138916</comments>
            <pubDate>Fri, 01 Oct 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4138916</guid>        </item>
        <item>
            <title>A graph-based algorithm for mining multi-level patterns in genomic data.</title>
            <link>http://www.medworm.com/index.php?rid=4122723&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20981888%26dopt%3DAbstract</link>
            <description>Authors: Lam WW, Chan KC, Chiu DK, Wong AK
    Comparative genomics is concerned with the study of genome structure and function of different species. It can provide useful information for the derivation of evolutionary and functional relationships between genomes. Previous work on genome comparison focuses mainly on comparing the entire genomes for visualization without further analysis. As many interesting patterns may exist between genomes and may lead to the discovering of functional gene segments (groups of genes), we propose an algorithm called Multi-Level Genome Comparison Algorithm (MGC) that can be used to facilitate the analysis of genomes at multi-levels during the comparison process to discover sequential and regional consistency in gene segments. Different genomes may have com...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4122723</comments>
            <pubDate>Fri, 01 Oct 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4122723</guid>        </item>
        <item>
            <title>Relative von neumann entropy for evaluating amino Acid conservation.</title>
            <link>http://www.medworm.com/index.php?rid=4122722&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20981889%26dopt%3DAbstract</link>
            <description>Authors: Johansson F, Toh H
    The Shannon entropy is a common way of measuring conservation of sites in multiple sequence alignments, and has also been extended with the relative Shannon entropy to account for background frequencies. The von Neumann entropy is another extension of the Shannon entropy, adapted from quantum mechanics in order to account for amino acid similarities. However, there is yet no relative von Neumann entropy defined for sequence analysis. We introduce a new definition of the von Neumann entropy for use in sequence analysis, which we found to perform better than the previous definition. We also introduce the relative von Neumann entropy and a way of parametrizing this in order to obtain the Shannon entropy, the relative Shannon entropy and the von Neumann entropy ...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4122722</comments>
            <pubDate>Fri, 01 Oct 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4122722</guid>        </item>
        <item>
            <title>Fuzzyart neural network for protein classification.</title>
            <link>http://www.medworm.com/index.php?rid=4122721&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20981890%26dopt%3DAbstract</link>
            <description>Authors: Angadi UB, Venkatesulu M
    One of the major research directions in bioinformatics is that of predicting the protein superfamily in large databases and classifying a given set of protein domains into superfamilies. The classification reflects the structural, evolutionary and functional relatedness. These relationships are embodied in hierarchical classification such as Structural Classification of Protein (SCOP), which is manually curated. Such classification is essential for the structural and functional analysis of proteins. Yet, a large number of proteins remain unclassified. We have proposed an unsupervised machine-learning FuzzyART neural network algorithm to classify a given set of proteins into SCOP superfamilies. The proposed method is fast learning and uses an atypical n...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4122721</comments>
            <pubDate>Fri, 01 Oct 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4122721</guid>        </item>
        <item>
            <title>Computational gene knockout reveals transdisease-transgene association structure.</title>
            <link>http://www.medworm.com/index.php?rid=4122720&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20981891%26dopt%3DAbstract</link>
            <description>Authors: Matsunaga T, Kuwata S, Muramatsu M
    Genome-wide association studies for a variety of diseases are identifying increasing numbers of candidate genes. Now we are confronted with the fact that some genes are common candidates across diseases. Thus there is a strong need to develop a hypothesis formulation methodology to comprehend multifaceted associations between genes and diseases. We have developed a computational method for building transdisease-transgene association structure. By introducing the basic rationale underlying the gene knockout approach as an information processing procedure to a network constructed on the basis of hyperlinks between disease and gene pages listed in the Online Mendelian Inheritance in Man (OMIM) database, relations of genes with diseases are compu...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4122720</comments>
            <pubDate>Fri, 01 Oct 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4122720</guid>        </item>
        <item>
            <title>Protein secondary structure prediction using NMR chemical shift data.</title>
            <link>http://www.medworm.com/index.php?rid=4122719&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20981892%26dopt%3DAbstract</link>
            <description>Authors: Zhao Y, Alipanahi B, Li SC, Li M
    Accurate determination of protein secondary structure from the chemical shift information is a key step for NMR tertiary structure determination. Relatively few work has been done on this subject. There needs to be a systematic investigation of algorithms that are (a) robust for large datasets; (b) easily extendable to (the dynamic) new databases; and (c) approaching to the limit of accuracy. We introduce new approaches using k-nearest neighbor algorithm to do the basic prediction and use the BCJR algorithm to smooth the predictions and combine different predictions from chemical shifts and based on sequence information only. Our new system, SUCCES, improves the accuracy of all existing methods on a large dataset of 805 proteins (at 86% Q(3) ac...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4122719</comments>
            <pubDate>Fri, 01 Oct 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4122719</guid>        </item>
        <item>
            <title>ANALYSIS OF qPCR DATA BY CONVERTING EXPONENTIALLY RELATED Ct VALUES INTO LINEARLY RELATED X(0) VALUES.</title>
            <link>http://www.medworm.com/index.php?rid=4122718&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20981893%26dopt%3DAbstract</link>
            <description>Authors: Thomsen R, Sølvsten CA, Linnet TE, Blechingberg J, Nielsen AL
    A common method for calculating results from qPCR experiments is the comparative Ct method, also called the 2(-ΔΔCt) method. However, several assumptions are included in the 2(-ΔΔCt) method and standard statistical analyses are not directly applicable. Here, we describe a different method, the X(0) method, for result calculations and statistical analysis from qPCR experiments. The X(0) method differs from the 2(-ΔΔCt) method by introducing a conversion of the exponentially related Ct values into linearly related X(0) values, which represent the amount of starting material in a qPCR experiment. Results calculated by the X(0) method are illustrated for qPCR experiments with technical and biological replicates, ...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4122718</comments>
            <pubDate>Fri, 01 Oct 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4122718</guid>        </item>
        <item>
            <title>Improving the inter-corpora compatibility for protein annotations.</title>
            <link>http://www.medworm.com/index.php?rid=4122717&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20981894%26dopt%3DAbstract</link>
            <description>Authors: Wang Y, Kim JD, Sætre R, Pyysalo S, Ohta T, Tsujii J
    Although there are several corpora with protein annotation, incompatibility between the annotations in different corpora remains a problem that hinders the progress of automatic recognition of protein names in biomedical literature. Here, we report on our efforts to find a solution to the incompatibility issue, and to improve the compatibility between two representative protein-annotated corpora: the GENIA corpus and the GENETAG corpus. In a comparative study, we improve our insight into the two corpora, and a series of experimental results show that most of the incompatibility can be removed.
    PMID: 20981894 [PubMed - in process] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4122717</comments>
            <pubDate>Fri, 01 Oct 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4122717</guid>        </item>
        <item>
            <title>A re-evaluation of biomedical named entity-term relations.</title>
            <link>http://www.medworm.com/index.php?rid=4122716&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20981895%26dopt%3DAbstract</link>
            <description>Authors: Ohta T, Pyysalo S, Kim JD, Tsujii J
    Text mining can support the interpretation of the enormous quantity of textual data produced in biomedical field. Recent developments in biomedical text mining include advances in the reliability of the recognition of named entities (NEs) such as specific genes and proteins, as well as movement toward richer representations of the associations of NEs. We argue that this shift in representation should be accompanied by the adoption of a more detailed model of the relations holding between NEs and other relevant domain terms. As a step toward this goal, we study NE-term relations with the aim of defining a detailed, broadly applicable set of relation types based on accepted domain standard concepts for use in corpus annotation and domain infor...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4122716</comments>
            <pubDate>Fri, 01 Oct 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">4122716</guid>        </item>
        <item>
            <title>Deppdb--DNA electrostatic potential properties database: electrostatic properties of genome DNA.</title>
            <link>http://www.medworm.com/index.php?rid=4088156&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20556853%26dopt%3DAbstract</link>
            <description>Authors: Osypov AA, Krutinin GG, Kamzolova SG
    The electrostatic properties of genome DNA influence its interactions with different proteins, in particular, the regulation of transcription by RNA-polymerases. DEPPDB--DNA Electrostatic Potential Properties Database--was developed to hold and provide all available information on the electrostatic properties of genome DNA combined with its sequence and annotation of biological and structural properties of genome elements and whole genomes. Genomes in DEPPDB are organized on a taxonomical basis. Currently, the database contains all the completely sequenced bacterial and viral genomes according to NCBI RefSeq. General properties of the genome DNA electrostatic potential profile and principles of its formation are revealed. This potential cor...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4088156</comments>
            <pubDate>Mon, 31 May 2010 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">4088156</guid>        </item>
        <item>
            <title>Proceedings of the 4th International Moscow Conference on Computational Molecular Biology MCCMB'09. July 20-23, 2009. Moscow, Russia.</title>
            <link>http://www.medworm.com/index.php?rid=4088155&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20963933%26dopt%3DAbstract</link>
            <description>Authors: 
    
    PMID: 20963933 [PubMed - indexed for MEDLINE] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4088155</comments>
            <pubDate>Mon, 31 May 2010 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">4088155</guid>        </item>
        <item>
            <title>Introduction: 4th International Moscow Conference on Computational Molecular Biology MCCMB'09.</title>
            <link>http://www.medworm.com/index.php?rid=3691708&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20564834%26dopt%3DAbstract</link>
            <description>Authors: Gelfand MS
    
    PMID: 20564834 [PubMed - in process] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3691708</comments>
            <pubDate>Mon, 31 May 2010 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">3691708</guid>        </item>
        <item>
            <title>Flexibility and mobility in mesophilic and thermophilic homologous proteins from molecular dynamics and foldunfold method.</title>
            <link>http://www.medworm.com/index.php?rid=3673570&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20556851%26dopt%3DAbstract</link>
            <description>Authors: Mamonova TB, Glyakina AV, Kurnikova MG, Galzitskaya OV
    To function properly protein molecules require both flexibility and rigidity, therefore fast and accurate prediction of protein rigidity/flexibility is one of the important problems in protein science. In this work we used two theoretical approaches to determine flexible regions in four homologous pairs of proteins from thermophilic and mesophilic organisms. Protein pairs chosen in this study were selected to represent four typical folding classes. Our first approach, FoldUnfold, uses amino acid sequence and statistical information on the density of contacts of amino acids in tertiary structures of known globular proteins. The main advantages of such knowledge-based methodology are its computational speed and ability to ma...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3673570</comments>
            <pubDate>Mon, 31 May 2010 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">3673570</guid>        </item>
        <item>
            <title>A comparative analysis of folding pathways of thermophilic and mesophilic proteins by monte carlo simulations.</title>
            <link>http://www.medworm.com/index.php?rid=3673569&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20556852%26dopt%3DAbstract</link>
            <description>Authors: Glyakina AV, Galzitskaya OV
    In this work we have studied the folding pathways for four pairs of homologous proteins from thermophilic and mesophilic organisms from two different structural classes (class a, all-alpha proteins and class d, alpha + beta proteins) using Monte Carlo simulations. We have obtained 50 trajectories for each protein and followed the free-energy profile and the order of folding of secondary structure elements between the last occurrence of the completely unfolded state and the first occurrence of the completely folded state. It turns out that the period of successful crossing of the free-energy barrier between unfolded and folded states for 40-45 trajectories (80-90%) makes 10% of the total folding time for four proteins (1tzvA, 1eyvA, 351c, and 1t4aA) ...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3673569</comments>
            <pubDate>Mon, 31 May 2010 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">3673569</guid>        </item>
        <item>
            <title>Deppdb - DNA electrostatic potential properties database: electrostatic properties of genome DNA.</title>
            <link>http://www.medworm.com/index.php?rid=3673568&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20556853%26dopt%3DAbstract</link>
            <description>Authors: Osypov AA, Krutinin GG, Kamzolova SG
    The electrostatic properties of genome DNA influence its interactions with different proteins, in particular, the regulation of transcription by RNA-polymerases. DEPPDB - DNA Electrostatic Potential Properties Database - was developed to hold and provide all available information on the electrostatic properties of genome DNA combined with its sequence and annotation of biological and structural properties of genome elements and whole genomes. Genomes in DEPPDB are organized on a taxonomical basis. Currently, the database contains all the completely sequenced bacterial and viral genomes according to NCBI RefSeq. General properties of the genome DNA electrostatic potential profile and principles of its formation are revealed. This potential c...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3673568</comments>
            <pubDate>Mon, 31 May 2010 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">3673568</guid>        </item>
        <item>
            <title>Empirical potentials for ion binding in proteins.</title>
            <link>http://www.medworm.com/index.php?rid=3673567&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20556854%26dopt%3DAbstract</link>
            <description>Authors: Rahmanov S, Kulakovskiy I, Uroshlev L, Makeev V
    Empirical potentials for interaction of proteins with intracellular ions are presented. We derive the potentials using a training dataset of the protein 3D structure bank, PDB, based on the statistical analysis of contacts between ions and protein atoms of different types. The potentials are derived using Monte Carlo Reference State, simulating non-interacting structure elements as random 3D points in the structure space. The resulting potentials are detailed, continuous, and cover a wide range of contact distances. The obtained potentials were tested for prediction of ion-binding sites in proteins and are shown to reproduce locations and specificities of ion-binding sites with a high accuracy. A web server is created for predict...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3673567</comments>
            <pubDate>Mon, 31 May 2010 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">3673567</guid>        </item>
        <item>
            <title>Gh101 family of glycoside hydrolases: subfamily structure and evolutionary connections with other families.</title>
            <link>http://www.medworm.com/index.php?rid=3673566&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20556855%26dopt%3DAbstract</link>
            <description>Authors: Naumoff DG
    The GH101 family is composed of endo-alpha-N-acetylgalactosaminidases and their homologues. Pairwise sequence comparison and phylogenetic analysis allowed us to distinguish five to six subfamilies in this family. Diverse domain structures were found among the family members. Usually they have five irreplaceable and some optional domains. Iterative screening of the protein database revealed an evolutionary relationship of the GH101 catalytic domain with glycoside hydrolase domains from GH13, GH31, and GH70 families. Among other homologous proteins we have found representatives of COG1649, as well as members of four new families of predicted glycoside hydrolases (GHL1-GHL4).
    PMID: 20556855 [PubMed - in process] (Source: Journal of Bioinformatics and Computational ...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3673566</comments>
            <pubDate>Mon, 31 May 2010 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">3673566</guid>        </item>
        <item>
            <title>Identification of conserved features of laglidadg homing endonucleases.</title>
            <link>http://www.medworm.com/index.php?rid=3673561&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20556856%26dopt%3DAbstract</link>
            <description>Authors: Grishin A, Fonfara I, Alexeevski A, Spirin S, Zanegina O, Karyagina A, Alexeyevsky D, Wende W
    LAGLIDADG family of homing endonucleases are rare-cutting enzymes which recognize long target sequences and are of great interest in genome engineering. Despite advances in homing endonuclease engineering, effective methods of broadening the range of cleaved sequences are still lacking. Here, we present a study of conserved structural features of LAGLIDADG homing endonucleases that might aid further development of such methods. The protein-DNA interface of LAGLIDADG homing endonucleases differs considerably with the particular nuclease, and the analysis of conserved protein-DNA interactions could not identify any residues crucial for DNA binding and common to most nucleases of the fam...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3673561</comments>
            <pubDate>Mon, 31 May 2010 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">3673561</guid>        </item>
        <item>
            <title>INTERACTION OF ANTIBODIES WITH AROMATIC LIGANDS: THE ROLE OF pi-STACKING.</title>
            <link>http://www.medworm.com/index.php?rid=3673560&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20556857%26dopt%3DAbstract</link>
            <description>Authors: Arzhanik V, Svistunova D, Koliasnikov O, Egorov AM
    Antibodies are responsible for antigen recognition in vertebrate organisms. Practically any molecule can be bound by antibodies. In this work structures of 73 complexes of antibodies with small antigens were taken from PDB database and compared. The main epitope of studied ligands was an aromatic ring. Antibodies bound it with a deep cavity, lying between complementary determining regions (CDR) H3 and L3 and formed by aromatic residues. In most cases the aromatic ring of ligand was placed parallel to one or two aromatic sidechains of binding site at 3.5-4 Angstrom distance. This disposition of aromatic rings is a sign of the presence of pi-stacking. It was found that small ligands with aromatics area percentage &amp;gt; 36% predom...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3673560</comments>
            <pubDate>Mon, 31 May 2010 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">3673560</guid>        </item>
        <item>
            <title>A parallel scheme for comparing transcription factor binding sites matrices.</title>
            <link>http://www.medworm.com/index.php?rid=3673559&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20556858%26dopt%3DAbstract</link>
            <description>Authors: Carat S, Houlgatte R, Bourdon J
    Gene regulation implies many mechanisms. Their identification is a crucial task to construct regulatory networks, and is necessary to understand the pathology in many cases. This requires the identification of transcription factors that play a role in regulation. Numerous motif discovery tools are now available. Combining efficiently their results appears useful for comparing and clustering these motifs in order to reduce redundancies and to identify the corresponding transcription factor. We develop a method that produces, compares and clusters a set of motifs and identifies some close motifs in databases like JASPAR and the public version of Transfac. Unlike previous comparison methods, where each matrix column is compared independently, we ha...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3673559</comments>
            <pubDate>Mon, 31 May 2010 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">3673559</guid>        </item>
        <item>
            <title>Malakite: an automatic tool for characterisation of structure of reliable blocks in multiple alignments of protein sequences.</title>
            <link>http://www.medworm.com/index.php?rid=3673558&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20556859%26dopt%3DAbstract</link>
            <description>Authors: Burkov B, Nagaev B, Spirin S, Alexeevski A
    It makes sense to speak of alignment of protein sequences only within the regions, where the sequences are related to each other. This simple consideration is often disregarded by programs of multiple alignment construction. A package for alignment analysis MAlAKiTE (Multiple Alignment Automatic Kinship Tiling Engine) is introduced. It aims to find the blocks of reliable alignment, which contain related regions only, within the whole alignment and allows for dealing with them. The validity of the detection of reliable blocks' was verified by comparison with structural data.
    PMID: 20556859 [PubMed - in process] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3673558</comments>
            <pubDate>Mon, 31 May 2010 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">3673558</guid>        </item>
        <item>
            <title>Exclusive sequences of different genomes.</title>
            <link>http://www.medworm.com/index.php?rid=3673557&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20556860%26dopt%3DAbstract</link>
            <description>Authors: Mitrofanov SI, Panchin AY, Spirin SA, Alexeevski AV, Panchin YV
    We studied the distribution of 1-7 bp words in a dataset that includes 139 complete eukaryotic genomes, 33 masked eukaryotic genomes and coding regions from 35 genomes. We tested different statistical models to determine over- and under-represented words. The method described by Karlin et al. has the strongest predictive power compared to other methods. Using this method we identified over- and under-represented words consistent within a large array of taxonomic groups. Some of those words have not yet been described as exclusive. For example, CGCG is over-represented in CG-deficient organisms. We also describe exceptions for widely known exclusive words, such as CG and TA.
    PMID: 20556860 [PubMed - in process]...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3673557</comments>
            <pubDate>Mon, 31 May 2010 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">3673557</guid>        </item>
        <item>
            <title>Genetack: frameshift identification in protein-coding sequences by the viterbi algorithm.</title>
            <link>http://www.medworm.com/index.php?rid=3673556&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20556861%26dopt%3DAbstract</link>
            <description>We describe a new program for ab initio frameshift detection in protein-coding nucleotide sequences. The task is to distinguish the same strand overlapping ORFs that occur in the sequence due to a presence of a frameshifted gene from the same strand overlapping ORFs that encompass true overlapping or adjacent genes. The GeneTack program uses a hidden Markov model (HMM) of genomic sequence with possibly frameshifted protein-coding regions. The Viterbi algorithm finds the maximum likelihood path that discriminates between true adjacent genes and those adjacent protein-coding regions that just appear to be separate entities due to frameshifts. Therefore, the program can identify spurious predictions made by a conventional gene-finding program misled by a frameshift. We tested GeneTack as well...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3673556</comments>
            <pubDate>Mon, 31 May 2010 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">3673556</guid>        </item>
        <item>
            <title>Probe-level universal search (plus) algorithm for gender differentiation in affymetrix datasets.</title>
            <link>http://www.medworm.com/index.php?rid=3673555&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20556862%26dopt%3DAbstract</link>
            <description>Authors: Karyagyna AS, Vassiliev MO, Ershova AS, Nurtdinov RN, Lossev IS
    Affymetrix microarrays measure gene expression based on the intensity of hybridization of a panel of oligonucleotide probes (probe set) with mRNA. The signals from all probes within a probe set are converted into a single measure that represents the expression value of a gene. This step diminishes the number of independently measured parameters and eliminates from consideration individual &quot;good-working&quot; probes. We propose a new feature selection algorithm (Probe Level Universal Search or PLUS algorithm) for probe-level analysis of gene expression datasets. The algorithm evaluates the intensities of perfect-match Affymetrix probes individually and selects probes that allow one to distinguish two given classes of sa...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3673555</comments>
            <pubDate>Mon, 31 May 2010 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">3673555</guid>        </item>
        <item>
            <title>Statistical comparison of methods to estimate the error probability in short-read illumina sequencing.</title>
            <link>http://www.medworm.com/index.php?rid=3673554&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20556863%26dopt%3DAbstract</link>
            <description>Authors: Abnizova I, Skelly T, Naumenko F, Whiteford N, Brown C, Cox T
    As was the case in the beginning of the sequencing era, the new generation of short-read sequencing technologies still requires both accuracy of data processing methods and reliable measures of that accuracy. Inspired by the classic of the genre, the Phred method, we generalized those findings in the area of base quality value calibration. We introduce a simple, straightforward statistically established way to measure the performance of a calibrator, and to find an optimal way to assess its reliability. We illustrate the method by assessing the performance of several calibrators/predictors for Illumina, Genome Analyser 2 (GA2) data. The choice of the best predictor is based on optimization of validity, discriminativ...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3673554</comments>
            <pubDate>Mon, 31 May 2010 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">3673554</guid>        </item>
        <item>
            <title>Computational approaches for drug repositioning and combination therapy design.</title>
            <link>http://www.medworm.com/index.php?rid=3673553&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20556864%26dopt%3DAbstract</link>
            <description>We describe a novel computational workflow for designing therapy using Ariadne Genomics Pathway Studio software. We use publically available microarray experiments for glioblastoma and automatically constructed ResNet and ChemEffect databases to exemplify how to find potentially effective chemicals for glioblastoma - the disease yet without effective treatment. Our first approach involved construction of signaling pathway affected in glioblastoma using scientific literature and data available in ResNet database. Compounds known to affect multiple proteins in this pathway were found in ChemEffect database. Another approach involved analysis of differential expression in glioblastoma patients using Sub-Network Enrichment Analysis (SNEA). SNEA identified angiogenesis-related protein Cyr61 as ...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3673553</comments>
            <pubDate>Mon, 31 May 2010 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">3673553</guid>        </item>
        <item>
            <title>Snps in the hiv-1 tata box and the AIDS pandemic.</title>
            <link>http://www.medworm.com/index.php?rid=3673552&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20556865%26dopt%3DAbstract</link>
            <description>Authors: Suslov VV, Ponomarenko PM, Efimov VM, Savinkova LK, Ponomarenko MP, Kolchanov NA
    Evolutionary trends have been examined in 146 HIV-1 forms (2662 copies, 2311 isolates) polymorphic for the TATA box using the &quot;DNA sequence--&amp;gt;affinity for TBP&quot; regression (TBP is the TATA binding protein). As a result, a statistically significant excess of low-affinity TATA box HIV-1 variants corresponding to a low level of both basal and TAT-dependent expression and, consequently, slow replication of HIV-1 have been detected. A detailed analysis revealed that the excess of slowly replicating HIV-1 is associated with the subtype E-associated TATA box core sequence &quot;CATAAAA&quot;. Principal Component Analysis performed on 2662 HIV-1 TATA box copies in 70 countries revealed the presence of two princip...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3673552</comments>
            <pubDate>Mon, 31 May 2010 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">3673552</guid>        </item>
        <item>
            <title>Comparative modeling of coevolution in communities of unicellular organisms: adaptability and biodiversity.</title>
            <link>http://www.medworm.com/index.php?rid=3673551&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20556866%26dopt%3DAbstract</link>
            <description>Authors: Lashin SA, Suslov VV, Matushkin YG
    We propose an original program &quot;Evolutionary constructor&quot; that is capable of computationally efficient modeling of both population-genetic and ecological problems, combining these directions in one model of required detail level. We also present results of comparative modeling of stability, adaptability and biodiversity dynamics in populations of unicellular haploid organisms which form symbiotic ecosystems. The advantages and disadvantages of two evolutionary strategies of biota formation - a few generalists' taxa-based biota formation and biodiversity-based biota formation - are discussed.
    PMID: 20556866 [PubMed - in process] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3673551</comments>
            <pubDate>Mon, 31 May 2010 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">3673551</guid>        </item>
        <item>
            <title>Wrestling with biomedical research results: language resources and literature analysis. Introduction.</title>
            <link>http://www.medworm.com/index.php?rid=3673571&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20183878%26dopt%3DAbstract</link>
            <description>Authors: Rebholz-Schuhmann D, Collier N, Park JC, Wong L
    
    PMID: 20183878 [PubMed - indexed for MEDLINE] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3673571</comments>
            <pubDate>Mon, 01 Feb 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3673571</guid>        </item>
        <item>
            <title>TEMPERATURE-DEPENDENT STRUCTURAL VARIABILITY OF RNAs: SPLICED LEADER RNAs AND THEIR EVOLUTIONARY HISTORY.</title>
            <link>http://www.medworm.com/index.php?rid=3312137&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20183871%26dopt%3DAbstract</link>
            <description>Authors: Marz M, Vanzo N, Stadler PF
    The structures attained by RNA molecules depend not only on their sequence but also on environmental parameters such as their temperature. So far, this effect has been largely neglected in bioinformatics studies. Here, we show that structural comparisons can be facilitated and more coherent structural models can be obtained when differences in environmental parameters are taken into account. We re-evaluate the secondary structures of the spliced leader (SL) RNAs from the seven eukaryotic phyla in which SL RNA trans-splicing has been described. Adjusting structure prediction to the natural growth temperatures and considering energetically similar secondary structures, we observe striking similarities among Euglenida, Kinetoplastida, Dinophyceae, Cnid...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3312137</comments>
            <pubDate>Mon, 01 Feb 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3312137</guid>        </item>
        <item>
            <title>A multi-strategy approach to informative gene identification from gene expression data.</title>
            <link>http://www.medworm.com/index.php?rid=3312136&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20183872%26dopt%3DAbstract</link>
            <description>Authors: Liu Z, Phan S, Famili F, Pan Y, Lenferink AE, Cantin C, Collins C, O'Connor-McCourt MD
    An unsupervised multi-strategy approach has been developed to identify informative genes from high throughput genomic data. Several statistical methods have been used in the field to identify differentially expressed genes. Since different methods generate different lists of genes, it is very challenging to determine the most reliable gene list and the appropriate method. This paper presents a multi-strategy method, in which a combination of several data analysis techniques are applied to a given dataset and a confidence measure is established to select genes from the gene lists generated by these techniques to form the core of our final selection. The remainder of the genes that form the pe...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3312136</comments>
            <pubDate>Mon, 01 Feb 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3312136</guid>        </item>
        <item>
            <title>TOPTMH: TOPOLOGY PREDICTOR FOR TRANSMEMBRANE alpha-HELICES.</title>
            <link>http://www.medworm.com/index.php?rid=3312135&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20183873%26dopt%3DAbstract</link>
            <description>We present TOPTMH, a new transmembrane helix topology prediction method that combines support vector machines, hidden Markov models, and a widely used rule-based scheme. The contribution of this work is the development of a prediction approach that first uses a binary SVM classifier to predict the helix residues and then it employs a pair of HMM models that incorporate the SVM predictions and hydropathy-based features to identify the entire transmembrane helix segments by capturing the structural characteristics of these proteins. TOPTMH outperforms state-of-the-art prediction methods and achieves the best performance on an independent static benchmark.
    PMID: 20183873 [PubMed - in process] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3312135</comments>
            <pubDate>Mon, 01 Feb 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3312135</guid>        </item>
        <item>
            <title>A quantum-inspired genetic algorithm based on probabilistic coding for multiple sequence alignment.</title>
            <link>http://www.medworm.com/index.php?rid=3312134&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20183874%26dopt%3DAbstract</link>
            <description>Authors: Huo HW, Stojkovic V, Xie QL
    Quantum parallelism arises from the ability of a quantum memory register to exist in a superposition of base states. Since the number of possible base states is 2(n), where n is the number of qubits in the quantum memory register, one operation on a quantum computer performs what an exponential number of operations on a classical computer performs. The power of quantum algorithms comes from taking advantages of quantum parallelism. Quantum algorithms are exponentially faster than classical algorithms. Genetic optimization algorithms are stochastic search algorithms which are used to search large, nonlinear spaces where expert knowledge is lacking or difficult to encode. QGMALIGN - a probabilistic coding based quantum-inspired genetic algorithm for m...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3312134</comments>
            <pubDate>Mon, 01 Feb 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3312134</guid>        </item>
        <item>
            <title>Mining disease state converters for medical intervention of diseases.</title>
            <link>http://www.medworm.com/index.php?rid=3312133&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20183875%26dopt%3DAbstract</link>
            <description>Authors: Dong G, Duan L, Tang C
    In applications such as gene therapy and drug design, a key goal is to convert the disease state of diseased objects from an undesirable state into a desirable one. Such conversions may be achieved by changing the values of some attributes of the objects. For example, in gene therapy one may convert cancerous cells to normal ones by changing some genes' expression level from low to high or from high to low. In this paper, we define the disease state conversion problem as the discovery of disease state converters; a disease state converter is a small set of attribute value changes that may change an object's disease state from undesirable into desirable. We consider two variants of this problem: personalized disease state converter mining mines disease st...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3312133</comments>
            <pubDate>Mon, 01 Feb 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3312133</guid>        </item>
        <item>
            <title>Identifying co-regulating microrna groups.</title>
            <link>http://www.medworm.com/index.php?rid=3312132&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20183876%26dopt%3DAbstract</link>
            <description>Conclusions: This work identifies highly probable co-regulating miRNAs, which are refined from the prediction by computational tools using (1) signal-to-noise ratio to get high accurate regulating miRNAs for every gene, and (2) Gene Ontology to obtain functional related co-regulating miRNA groups. Our result has partly been supported by biological experiments. Based on prediction by TargetScanS, we found highly probable target gene groups in the Supplementary Information. This result might help biologists to find small set of miRNAs for genes of interest rather than huge amount of miRNA set. Supplementary Information: http://www.deakin.edu.au/~phoebe/JBCBAnChen/JBCB.htm.
    PMID: 20183876 [PubMed - in process] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3312132</comments>
            <pubDate>Mon, 01 Feb 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3312132</guid>        </item>
        <item>
            <title>Is lgi2 the candidate gene for partial epilepsy with pericentral spikes?</title>
            <link>http://www.medworm.com/index.php?rid=3312131&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20183877%26dopt%3DAbstract</link>
            <description>Authors: Limviphuvadh V, Chua LL, Eisenhaber F, Adhikari S, Maurer-Stroh S
    Partial epilepsy with pericentral spikes (PEPS) is a familial epilepsy with disease locus mapped to human chromosome region 4p15; yet, the causative gene is unknown. In this work, arguments based on protein sequence analysis and patient-specific chromosomal deletions are provided for LGI2 as the prime candidate gene for PEPS among the 52 genes known at the genome locus 4p15. Furthermore, we suggest that two reports of patients that were not classified as PEPS but show very similar phenotypes and deletions in the PEPS disease locus, could in fact describe the same disease. To test this hypothesis, patients with diagnosed PEPS or the described similar phenotypes could be screened for mutations in LGI2 and other sh...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3312131</comments>
            <pubDate>Mon, 01 Feb 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3312131</guid>        </item>
        <item>
            <title>Wrestling with biomedical research results: language resources and literature analysis.</title>
            <link>http://www.medworm.com/index.php?rid=3312130&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20183878%26dopt%3DAbstract</link>
            <description>WRESTLING WITH BIOMEDICAL RESEARCH RESULTS: LANGUAGE RESOURCES AND LITERATURE ANALYSIS.
    J Bioinform Comput Biol. 2010 Feb;8(1):129-130
    Authors: Rebholz-Schuhmann D, Collier N, Park JC, Wong L
    No abstract received.
    PMID: 20183878 [PubMed - as supplied by publisher] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3312130</comments>
            <pubDate>Mon, 01 Feb 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3312130</guid>        </item>
        <item>
            <title>Event extraction with complex event classification using rich features.</title>
            <link>http://www.medworm.com/index.php?rid=3312129&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20183879%26dopt%3DAbstract</link>
            <description>EVENT EXTRACTION WITH COMPLEX EVENT CLASSIFICATION USING RICH FEATURES.
    J Bioinform Comput Biol. 2010 Feb;8(1):131-146
    Authors: Miwa M, S&amp;#xE6;tre R, Kim JD, Tsujii J
    Biomedical Natural Language Processing (BioNLP) attempts to capture biomedical phenomena from texts by extracting relations between biomedical entities (i.e. proteins and genes). Traditionally, only binary relations have been extracted from large numbers of published papers. Recently, more complex relations (biomolecular events) have also been extracted. Such events may include several entities or other relations. To evaluate the performance of the text mining systems, several shared task challenges have been arranged for the BioNLP community. With a common and consistent task setting, the BioNLP'09 shared task ev...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3312129</comments>
            <pubDate>Mon, 01 Feb 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3312129</guid>        </item>
        <item>
            <title>The value of an in-domain lexicon in genomics qa.</title>
            <link>http://www.medworm.com/index.php?rid=3312128&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20183880%26dopt%3DAbstract</link>
            <description>Authors: Sasaki Y, McNaught J, Ananiadou S
    This paper demonstrates that a large-scale lexicon tailored for the biology domain is effective in improving question analysis for genomics Question Answering (QA). We use the TREC Genomics Track data to evaluate the performance of different question analysis methods. It is hard to process textual information in biology, especially in molecular biology, due to a huge number of technical terms which rarely appear in general English documents and dictionaries. To support biological Text Mining, we have developed a domain-specific resource, the BioLexicon. Started in 2006 from scratch, this lexicon currently includes more than four million biomedical terms consisting of newly curated terms and terms collected from existing biomedical databases. W...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3312128</comments>
            <pubDate>Mon, 01 Feb 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3312128</guid>        </item>
        <item>
            <title>Calbc silver standard corpus.</title>
            <link>http://www.medworm.com/index.php?rid=3312127&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20183881%26dopt%3DAbstract</link>
            <description>Authors: Rebholz-Schuhmann D, Yepes AJ, VAN Mulligen EM, Kang N, Kors J, Milward D, Corbett P, Buyko E, Beisswanger E, Hahn U
    The CALBC initiative aims to provide a large-scale biomedical text corpus that contains semantic annotations for named entities of different kinds. The generation of this corpus requires that the annotations from different automatic annotation systems be harmonized. In the first phase, the annotation systems from five participants (EMBL-EBI, EMC Rotterdam, NLM, JULIE Lab Jena, and Linguamatics) were gathered. All annotations were delivered in a common annotation format that included concept identifiers in the boundary assignments and that enabled comparison and alignment of the results. During the harmonization phase, the results produced from those different sy...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3312127</comments>
            <pubDate>Mon, 01 Feb 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3312127</guid>        </item>
        <item>
            <title>Analysis of mesenchymal stem cell differentiation in vitro using classification association rule mining.</title>
            <link>http://www.medworm.com/index.php?rid=3312145&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20014470%26dopt%3DAbstract</link>
            <description>Authors: Wang W, Wang YJ, Ba&amp;#xF1;ares-Alc&amp;#xE1;ntara R, Coenen F, Cui Z
    In this paper, data mining is used to analyze the data on the differentiation of mammalian Mesenchymal Stem Cells (MSCs), aiming at discovering known and hidden rules governing MSC differentiation, following the establishment of a web-based public database containing experimental data on the MSC proliferation and differentiation. To this effect, a web-based public interactive database comprising the key parameters which influence the fate and destiny of mammalian MSCs has been constructed and analyzed using Classification Association Rule Mining (CARM) as a data-mining technique. The results show that the proposed approach is technically feasible and performs well with respect to the accuracy of (classification) p...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3312145</comments>
            <pubDate>Tue, 01 Dec 2009 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3312145</guid>        </item>
        <item>
            <title>On the asymmetry of the residue compositions of the binding sites on protein surfaces.</title>
            <link>http://www.medworm.com/index.php?rid=3312144&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20014471%26dopt%3DAbstract</link>
            <description>Authors: Iv&amp;#xE1;n G, Szabadka Z, Grolmusz V
    By screening all the ligand binding sites in the Protein Data Bank, we have found that while it is geometrically possible that a loop, formed from a protein chain with residues ZYX, would &quot;impersonate&quot; another chain-loop with residues XYZ by a simple twisting of either the loop or the bound ligand, it almost never happens. This fact is rather surprising, and implies a notable asymmetry, since (i) loops in the folded proteins sometimes can be flexible enough to be twisted, but (ii) ligands are almost always extremely mobile before binding to the protein, therefore they can turn around and bind to residue-sequence ZYX as well. Data availability: The supplementary Table 3 lists the appearances of the residue-sequences and their inverses in the ...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3312144</comments>
            <pubDate>Tue, 01 Dec 2009 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3312144</guid>        </item>
        <item>
            <title>Dimension reduction of microarray gene expression data: the accelerated failure time model.</title>
            <link>http://www.medworm.com/index.php?rid=3312143&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20014472%26dopt%3DAbstract</link>
            <description>Authors: Nguyen TS, Rojo J
    The construction of the components of Partial Least Squares (PLS) is based on the maximization of the covariance/correlation between linear combinations of the predictors and the response. However, the usual Pearson correlation is influenced by outliers in the response or in the predictors. To cope with outliers, we replace the Pearson correlation with the Spearman rank correlation in the optimization criteria of PLS. The rank-based method of PLS is insensitive to outlying values in both the predictors and response, and incorporates the censoring information by using an approach of Nguyen and Rocke (2004) and two approaches of reweighting and mean imputation of Datta et al. (2007). The performance of the rank-based approaches of PLS, denoted by Rank-based Mod...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3312143</comments>
            <pubDate>Tue, 01 Dec 2009 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3312143</guid>        </item>
        <item>
            <title>A probabilistic framework to improve microrna target prediction by incorporating proteomics data.</title>
            <link>http://www.medworm.com/index.php?rid=3312142&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20014473%26dopt%3DAbstract</link>
            <description>Authors: Li J, Min R, Bonner A, Zhang Z
    Due to the difficulties in identifying microRNA (miRNA) targets experimentally in a high-throughput manner, several computational approaches have been proposed. To this date, most leading algorithms are based on sequence information alone. However, there has been limited overlap between these predictions, implying high false-positive rates, which underlines the limitation of sequence-based approaches. Considering the repressive nature of miRNAs at the mRNA translational level, here we describe a probabilistic model to make predictions by combining sequence complementarity, miRNA expression level, and protein abundance. Our underlying assumption is that, given sequence complementarity between a miRNA and its putative mRNA targets, the miRNA expres...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3312142</comments>
            <pubDate>Tue, 01 Dec 2009 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3312142</guid>        </item>
        <item>
            <title>Sirius PSB: a generic system for analysis of biological sequences.</title>
            <link>http://www.medworm.com/index.php?rid=3312141&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20014474%26dopt%3DAbstract</link>
            <description>Authors: Koh CH, Lin S, Jedd G, Wong L
    Computational tools are essential components of modern biological research. For example, BLAST searches can be used to identify related proteins based on sequence homology, or when a new genome is sequenced, prediction models can be used to annotate functional sites such as transcription start sites, translation initiation sites and polyadenylation sites and to predict protein localization. Here we present Sirius Prediction Systems Builder (PSB), a new computational tool for sequence analysis, classification and searching. Sirius PSB has four main operations: (1) Building a classifier, (2) Deploying a classifier, (3) Search for proteins similar to query proteins, (4) Preliminary and post-prediction analysis. Sirius PSB supports all these operation...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3312141</comments>
            <pubDate>Tue, 01 Dec 2009 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3312141</guid>        </item>
        <item>
            <title>In silico screening of protein-protein interactions with all-to-all rigid docking and clustering: an application to pathway analysis.</title>
            <link>http://www.medworm.com/index.php?rid=3312140&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20014475%26dopt%3DAbstract</link>
            <description>Authors: Matsuzaki Y, Matsuzaki Y, Sato T, Akiyama Y
    We propose a computational screening system of protein-protein interactions using tertiary structure data. Our system combines all-to-all protein docking and clustering to find interacting protein pairs. We tuned our prediction system by applying various parameters and clustering algorithms and succeeded in outperforming previous methods. This method was also applied to a biological pathway estimation problem to show its use in network level analysis. The structural data were collected from the Protein Data Bank, PDB. Then all-to-all docking among target protein structures was conducted using a conventional protein-protein docking software package, ZDOCK. The highest-ranked 2000 decoys were clustered based on structural similarity am...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3312140</comments>
            <pubDate>Tue, 01 Dec 2009 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3312140</guid>        </item>
        <item>
            <title>Inference of gene regulatory networks using boolean-network inference methods.</title>
            <link>http://www.medworm.com/index.php?rid=3312139&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20014476%26dopt%3DAbstract</link>
            <description>Authors: Hickman GJ, Hodgman TC
    The modeling of genetic networks especially from microarray and related data has become an important aspect of the biosciences. This review takes a fresh look at a specific family of models used for constructing genetic networks, the so-called Boolean networks. The review outlines the various different types of Boolean network developed to date, from the original Random Boolean Network to the current Probabilistic Boolean Network. In addition, some of the different inference methods available to infer these genetic networks are also examined. Where possible, particular attention is paid to input requirements as well as the efficiency, advantages and drawbacks of each method. Though the Boolean network model is one of many models available for network inf...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3312139</comments>
            <pubDate>Tue, 01 Dec 2009 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3312139</guid>        </item>
        <item>
            <title>Exploring the protein landscape in ramachandran space: it's not just psi-phi.</title>
            <link>http://www.medworm.com/index.php?rid=3312138&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20014477%26dopt%3DAbstract</link>
            <description>Authors: Krivan W, Carter D
    Most methods for the structural comparison of proteins utilize molecular coordinates in the three-dimensional physical space. Recently, a group has presented an elegant novel approach based on the characterization of protein shape in terms of backbone torsion angles. They have demonstrated considerable success in direct comparisons with other techniques, and their method lends itself to rapid screening of structural information from rapidly growing databases. We think that the torsion angle approach can be further strengthened by refining the distance notion that forms the basis of the computational scheme. In particular, we are suggesting to compute the distance along the path that minimizes the transition cost between aligned pairs of angles and therefore ...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3312138</comments>
            <pubDate>Tue, 01 Dec 2009 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3312138</guid>        </item>
        <item>
            <title>Search similar protein structures with classification, sequence and 3d alignments.</title>
            <link>http://www.medworm.com/index.php?rid=2839395&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19785044%26dopt%3DAbstract</link>
            <description>Authors: Lu Z, Zhao Z, Garcia S, Krishnaswamy K, Fu B
    We have developed an algorithm and web tool to search similar protein structures in the PDB (Protein Data Bank). The algorithm is a combination of a series of methods including protein classification, geometric feature extraction, sequence alignment, and 3D structure alignment. Given a protein structure, the tool can efficiently discover similar structures from hundreds of thousands of structures stored in the PDB. Our experimental results show that it is more accurate than other well-known protein search systems including PSI-BLAST, 3D-BLAST, and SSM in finding proteins that are structurally similar to the query protein, and its speed is also competitive with those systems. The algorithm has been fully implemented and is accessible...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2839395</comments>
            <pubDate>Tue, 29 Sep 2009 10:42:24 +0100</pubDate>
            <guid isPermaLink="false">2839395</guid>        </item>
        <item>
            <title>Protein fold classification with genetic algorithms and feature selection.</title>
            <link>http://www.medworm.com/index.php?rid=2839394&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19785045%26dopt%3DAbstract</link>
            <description>Authors: Chen P, Liu C, Burge L, Mahmood M, Southerland W, Gloster C
    Protein fold classification is a key step to predicting protein tertiary structures. This paper proposes a novel approach based on genetic algorithms and feature selection to classifying protein folds. Our dataset is divided into a training dataset and a test dataset. Each individual for the genetic algorithms represents a selection function of the feature vectors of the training dataset. A support vector machine is applied to each individual to evaluate the fitness value (fold classification rate) of each individual. The aim of the genetic algorithms is to search for the best individual that produces the highest fold classification rate. The best individual is then applied to the feature vectors of the test dataset a...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2839394</comments>
            <pubDate>Tue, 29 Sep 2009 10:42:21 +0100</pubDate>
            <guid isPermaLink="false">2839394</guid>        </item>
        <item>
            <title>Predicting local quality of a sequence-structure alignment.</title>
            <link>http://www.medworm.com/index.php?rid=2839393&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19785046%26dopt%3DAbstract</link>
            <description>We present two complementary techniques, FragQA and PosQA, to accurately predict local quality of a sequence-structure (i.e. sequence-template) alignment generated by comparative modeling (i.e. homology modeling and threading). FragQA and PosQA predict local quality from two different perspectives. Different from existing methods, FragQA directly predicts cRMSD between a continuously aligned fragment determined by an alignment and the corresponding fragment in the native structure, while PosQA predicts the quality of an individual aligned position. Both FragQA and PosQA use an SVM (Support Vector Machine) regression method to perform prediction using similar information extracted from a single given alignment. Experimental results demonstrate that FragQA performs well on predicting local f...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2839393</comments>
            <pubDate>Tue, 29 Sep 2009 10:42:19 +0100</pubDate>
            <guid isPermaLink="false">2839393</guid>        </item>
        <item>
            <title>Efficient simulation of ligand-receptor binding processes using the conformation dynamics approach.</title>
            <link>http://www.medworm.com/index.php?rid=2839392&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19785047%26dopt%3DAbstract</link>
            <description>Authors: Bujotzek A, Weber M
    The understanding of biological ligand-receptor binding processes is relevant for a variety of research topics and assists the rational design of novel drug molecules. Computer simulation can help to advance this understanding, but, due to the high dimensionality of according systems, suffers from the severe computational cost. Based on the framework provided by conformation dynamics and transition state theory, a novel heuristic approach of simulating ligand-receptor binding processes is introduced, which is not dependent on calculating lengthy molecular dynamics trajectories. First, the relevant portion of conformational space is partitioned with meshless methods. Then, each region is sampled separately, using hybrid Monte Carlo. Finally, the dynamical bi...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2839392</comments>
            <pubDate>Tue, 29 Sep 2009 10:42:16 +0100</pubDate>
            <guid isPermaLink="false">2839392</guid>        </item>
        <item>
            <title>Iterative two-pass algorithm for missing data imputation in SNP arrays.</title>
            <link>http://www.medworm.com/index.php?rid=2839391&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19785048%26dopt%3DAbstract</link>
            <description>Authors: Sinoquet C
    Though nowadays high-throughput genotyping techniques' quality improves, missing data still remains fairly common. Studies have shown that even a low percentage of missing SNPs is detrimental to the reliability of down-stream analyses such as SNP-disease association tests. This paper investigates the potentiality for improving the accuracy of an SNP inference method based on the algorithm formerly designed by Roberts and co-workers (NPUTE, 2007). This initial algorithm performs a single scan of an SNP array, inferring missing SNPs in the context of sliding windows. We have first designed a variant, KNNWinOpti, which fully exploits backward and forward dependencies between the overlapping windows and thus restores the genuine dependency of inference upon direction sc...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2839391</comments>
            <pubDate>Tue, 29 Sep 2009 10:42:13 +0100</pubDate>
            <guid isPermaLink="false">2839391</guid>        </item>
        <item>
            <title>A novel coherence measure for discovering scaling biclusters from gene expression data.</title>
            <link>http://www.medworm.com/index.php?rid=2839390&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19785049%26dopt%3DAbstract</link>
            <description>Authors: Mukhopadhyay A, Maulik U, Bandyopadhyay S
    Biclustering methods are used to identify a subset of genes that are co-regulated in a subset of experimental conditions in microarray gene expression data. Many biclustering algorithms rely on optimizing mean squared residue to discover biclusters from a gene expression dataset. Recently it has been proved that mean squared residue is only good in capturing constant and shifting biclusters. However, scaling biclusters cannot be detected using this metric. In this article, a new coherence measure called scaling mean squared residue (SMSR) is proposed. Theoretically it has been proved that the proposed new measure is able to detect the scaling patterns effectively and it is invariant to local or global scaling of the input dataset. The ...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2839390</comments>
            <pubDate>Tue, 29 Sep 2009 10:42:10 +0100</pubDate>
            <guid isPermaLink="false">2839390</guid>        </item>
        <item>
            <title>Asymptotics of canonical and saturated RNA secondary structures.</title>
            <link>http://www.medworm.com/index.php?rid=2839389&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19785050%26dopt%3DAbstract</link>
            <description>Authors: Clote P, Kranakis E, Krizanc D, Salvy B
    It is a classical result of Stein and Waterman that the asymptotic number of RNA secondary structures is 1.104366 . n(-3/2) . 2.618034(n). In this paper, we study combinatorial asymptotics for two special subclasses of RNA secondary structures - canonical and saturated structures. Canonical secondary structures are defined to have no lonely (isolated) base pairs. This class of secondary structures was introduced by Bompf&amp;#xFC;newerer et al., who noted that the run time of Vienna RNA Package is substantially reduced when restricting computations to canonical structures. Here we provide an explanation for the speed-up, by proving that the asymptotic number of canonical RNA secondary structures is 2.1614 . n(-3/2) . 1.96798(n) and that the ...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2839389</comments>
            <pubDate>Tue, 29 Sep 2009 10:42:07 +0100</pubDate>
            <guid isPermaLink="false">2839389</guid>        </item>
        <item>
            <title>A note on the calculation of N-statistics.</title>
            <link>http://www.medworm.com/index.php?rid=2839388&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19785051%26dopt%3DAbstract</link>
            <description>Authors: Almudevar A
    A class of statistics suitable for testing against equality of multivariate distributions is described by Klebanov and co-workers in 2007. Referred to as N-statistics, their discriminating ability is based on various forms of distance kernels in R(d), the intention being to capture distinct forms of deviation from equality. This makes them particularly suitable for large-scale genomic screening applications, in which such variety of alternatives can be anticipated. One of these kernels, denoted as L(4), introduces weighting by directional densities, hence the evaluation of L(4) requires integration on the unit sphere in R(d). In this note we introduce a methodology for the evaluation of integrals related to L(4). It is shown that for a class of directional densitie...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2839388</comments>
            <pubDate>Tue, 29 Sep 2009 10:42:04 +0100</pubDate>
            <guid isPermaLink="false">2839388</guid>        </item>
        <item>
            <title>Uniqueness, intractability and exact algorithms: reflections on level-k phylogenetic networks.</title>
            <link>http://www.medworm.com/index.php?rid=2646143&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19634194%26dopt%3DAbstract</link>
            <description>Authors: VAN Iersel L, Kelk S, Mnich M
    Phylogenetic networks provide a way to describe and visualize evolutionary histories that have undergone so-called reticulate evolutionary events such as recombination, hybridization or horizontal gene transfer. The level k of a network determines how non-treelike the evolution can be, with level-0 networks being trees. We study the problem of constructing level-k phylogenetic networks from triplets, i.e. phylogenetic trees for three leaves (taxa). We give, for each k, a level-k network that is uniquely defined by its triplets. We demonstrate the applicability of this result by using it to prove that (1) for all k &amp;gt;/= 1 it is NP-hard to construct a level-k network consistent with all input triplets, and (2) for all k &amp;gt;/= 0 it is NP-hard to c...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2646143</comments>
            <pubDate>Tue, 28 Jul 2009 21:18:34 +0100</pubDate>
            <guid isPermaLink="false">2646143</guid>        </item>
        <item>
            <title>The net-hmm approach: phylogenetic network inference by combining maximum likelihood and hidden markov models.</title>
            <link>http://www.medworm.com/index.php?rid=2646142&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19634195%26dopt%3DAbstract</link>
            <description>We describe the properties of the NET-HMM, devise efficient algorithms for solving a set of problems related to it, and implement them in software. We also provide a novel complementary significance test for evaluating the fitness of a model (NET-HMM) to a given dataset. Using NET-HMM, we are able to answer interesting biological questions, such as inferring the length of partial HGT's and the affected nucleotides in the genomic sequences, as well as inferring the exact location of HGT events along the tree branches. These advantages are demonstrated through the analysis of synthetical inputs and three different biological inputs.
    PMID: 19634195 [PubMed - in process] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2646142</comments>
            <pubDate>Tue, 28 Jul 2009 21:18:31 +0100</pubDate>
            <guid isPermaLink="false">2646142</guid>        </item>
        <item>
            <title>Curve-based clustering of time course gene expression data using self-organizing maps.</title>
            <link>http://www.medworm.com/index.php?rid=2646141&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19634196%26dopt%3DAbstract</link>
            <description>Authors: Chen X
    There is an increasing interest in clustering time course gene expression data to investigate a wide range of biological processes. However, developing a clustering algorithm ideal for time course gene express data is still challenging. As timing is an important factor in defining true clusters, a clustering algorithm shall explore expression correlations between time points in order to achieve a high clustering accuracy. Moreover, inter-cluster gene relationships are often desired in order to facilitate the computational inference of biological pathways and regulatory networks. In this paper, a new clustering algorithm called CurveSOM is developed to offer both features above. It first presents each gene by a cubic smoothing spline fitted to the time course expression ...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2646141</comments>
            <pubDate>Tue, 28 Jul 2009 21:18:28 +0100</pubDate>
            <guid isPermaLink="false">2646141</guid>        </item>
        <item>
            <title>Comparing pearson, spearman and hoeffding's d measure for gene expression association analysis.</title>
            <link>http://www.medworm.com/index.php?rid=2646140&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19634197%26dopt%3DAbstract</link>
            <description>Authors: Fujita A, Sato JR, Demasi MA, Sogayar MC, Ferreira CE, Miyano S
    DNA microarrays have become a powerful tool to describe gene expression profiles associated with different cellular states, various phenotypes and responses to drugs and other extra- or intra-cellular perturbations. In order to cluster co-expressed genes and/or to construct regulatory networks, definition of distance or similarity between measured gene expression data is usually required, the most common choices being Pearson's and Spearman's correlations. Here, we evaluate these two methods and also compare them with a third one, namely Hoeffding's D measure, which is used to infer nonlinear and non-monotonic associations, i.e. independence in a general sense. By comparing three different variable association app...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2646140</comments>
            <pubDate>Tue, 28 Jul 2009 21:18:25 +0100</pubDate>
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        <item>
            <title>Aliasing in gene feature detection by projective methods.</title>
            <link>http://www.medworm.com/index.php?rid=2646139&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19634198%26dopt%3DAbstract</link>
            <description>Authors: Capobianco E
    Because of measurements obtained under limited experimental conditions or time points compared to the presence of many genes, also known as the &quot;large dimension, small sample size&quot; problem, dimensionality reduction techniques are a common practice in statistical bioinformatics involving microarray analysis. However, in order to improve the performance of reverse engineering and statistical inference procedures aimed to estimate gene-gene connectivity links, some kind of regularization is usually needed to reduce the overall data complexities, together with ad hoc feature selection to uncover biologically relevant gene associations. The paper deals with feature selection by projective methods; in particular, it addresses some issues: Can the impact of noise on the ...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2646139</comments>
            <pubDate>Tue, 28 Jul 2009 21:18:23 +0100</pubDate>
            <guid isPermaLink="false">2646139</guid>        </item>
        <item>
            <title>Clustering-based approach for predicting motif pairs from protein interaction data.</title>
            <link>http://www.medworm.com/index.php?rid=2646138&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19634199%26dopt%3DAbstract</link>
            <description>Authors: Leung HC, Siu MH, Yiu SM, Chin FY, Sung KW
    Predicting motif pairs from a set of protein sequences based on the protein-protein interaction data is an important, but difficult computational problem. Tan et al. proposed a solution to this problem. However, the scoring function (using chi(2) testing) used in their approach is not adequate and their approach is also not scalable. It may take days to process a set of 5000 protein sequences with about 20,000 interactions. Later, Leung et al. proposed an improved scoring function and faster algorithms for solving the same problem. But, the model used in Leung et al. is complicated. The exact value of the scoring function is not easy to compute and an estimated value is used in practice. In this paper, we derive a better model to capt...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2646138</comments>
            <pubDate>Tue, 28 Jul 2009 21:18:13 +0100</pubDate>
            <guid isPermaLink="false">2646138</guid>        </item>
        <item>
            <title>Inference of large-scale gene regulatory networks using regression-based network approach.</title>
            <link>http://www.medworm.com/index.php?rid=2646137&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19634200%26dopt%3DAbstract</link>
            <description>In this study, we propose a simple procedure for constructing large scale gene regulatory networks using a regression-based network approach. We determine the optimal out-degree of network structure by using the sum of squared coefficients which are obtained from all appropriate regression models. Through the simulated data, accuracy of estimation and robustness against noise are computed in order to compare with the vector autoregressive regression model. Our method shows high accuracy and robustness for inferring large-scale gene networks. Also it is applied to Caulobacter crecentus cell cycle data consisting of 1472 genes. It shows that many genes are regulated by two transcription factors, ctrA and gcrA, that are known for global regulators.
    PMID: 19634200 [PubMed - in process] (So...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2646137</comments>
            <pubDate>Tue, 28 Jul 2009 21:18:11 +0100</pubDate>
            <guid isPermaLink="false">2646137</guid>        </item>
        <item>
            <title>A tutorial of techniques for improving standard hidden markov model algorithms.</title>
            <link>http://www.medworm.com/index.php?rid=2646136&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19634201%26dopt%3DAbstract</link>
            <description>Authors: Golod D, Brown DG
    In this tutorial, we discuss two main algorithms for Hidden Markov Models or HMMs: the Viterbi algorithm and the expectation phase of the Baum-Welch algorithm, and we describe ways to improve their na&amp;#xEF;ve implementations. For the Baum-Welch algorithm we first present an implementation of the expectation computations using constant space. We then discuss the classical implementation of this calculation and describe ways to reduce its space usage to logarithmic and $O(\sqrt n)$, with their respective CPU costs. We also note where each respective algorithm can be parallelized. For the Viterbi algorithm, we describe $O(\sqrt n)$ and logarithmic space algorithms which increase CPU use by a factor of two and by a logarithmic factor respectively. We also present...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2646136</comments>
            <pubDate>Tue, 28 Jul 2009 21:18:08 +0100</pubDate>
            <guid isPermaLink="false">2646136</guid>        </item>
        <item>
            <title>A fast and accurate algorithm for comparative analysis of metabolic pathways.</title>
            <link>http://www.medworm.com/index.php?rid=2473814&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19507283%26dopt%3DAbstract</link>
            <description>Authors: Ay F, Kahveci T, DE Cr&amp;#xE9;cy-Lagard V
    Pathways show how different biochemical entities interact with one another to perform vital functions for the survival of an organism. Comparative analysis of pathways is crucial in identifying functional similarities that are difficult to identify by comparing individual entities that build up these pathways. When interacting entities are of single type, the problem of identifying similarities by aligning the pathways can be reduced to graph isomorphism problem. For pathways with varying types of entities such as metabolic pathways, alignment problem is even more challenging. In order to simplify this problem, existing methods often reduce metabolic pathways to graphs with restricted topologies and single type of nodes. However, these a...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2473814</comments>
            <pubDate>Mon, 01 Jun 2009 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">2473814</guid>        </item>
        <item>
            <title>Efficient computation of kinship and identity coefficients on large pedigrees.</title>
            <link>http://www.medworm.com/index.php?rid=2473808&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19507284%26dopt%3DAbstract</link>
            <description>Authors: Cheng E, Elliott B, Ozsoyoglu ZM
    With the rapidly expanding field of medical genetics and genetic counseling, genealogy information is becoming increasingly abundant. An important computation on pedigree data is the calculation of identity coefficients, which provide a complete description of the degree of relatedness of a pair of individuals. The areas of application of identity coefficients are numerous and diverse, from genetic counseling to disease tracking, and thus, the computation of identity coefficients merits special attention. However, the computation of identity coefficients is not done directly, but rather as the final step after computing a set of generalized kinship coefficients. In this paper, we first propose a novel Path-Counting Formula for calculating gener...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2473808</comments>
            <pubDate>Mon, 01 Jun 2009 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">2473808</guid>        </item>
        <item>
            <title>An orfome assembly approach to metagenomics sequences analysis.</title>
            <link>http://www.medworm.com/index.php?rid=2473807&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19507285%26dopt%3DAbstract</link>
            <description>Authors: Ye Y, Tang H
    Metagenomics is an emerging methodology for the direct genomic analysis of a mixed community of uncultured microorganisms. The current analyses of metagenomics data largely rely on the computational tools originally designed for microbial genomics projects. The challenge of assembling metagenomic sequences arises mainly from the short reads and the high species complexity of the community. Alternatively, individual (short) reads will be searched directly against databases of known genes (or proteins) to identify homologous sequences. The latter approach may have low sensitivity and specificity in identifying homologous sequences, which may further bias the subsequent diversity analysis. In this paper, we present a novel approach to metagenomic data analysis, calle...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2473807</comments>
            <pubDate>Mon, 01 Jun 2009 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">2473807</guid>        </item>
        <item>
            <title>Graph wavelet alignment kernels for drug virtual screening.</title>
            <link>http://www.medworm.com/index.php?rid=2473806&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19507286%26dopt%3DAbstract</link>
            <description>Authors: Smalter A, Huan J, Lushington G
    In this paper, we introduce a novel statistical modeling technique for target property prediction, with applications to virtual screening and drug design. In our method, we use graphs to model chemical structures and apply a wavelet analysis of graphs to summarize features capturing graph local topology. We design a novel graph kernel function to utilize the topology features to build predictive models for chemicals via Support Vector Machine classifier. We call the new graph kernel a graph wavelet-alignment kernel. We have evaluated the efficacy of the wavelet-alignment kernel using a set of chemical structure-activity prediction benchmarks. Our results indicate that the use of the kernel function yields performance profiles comparable to, and ...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2473806</comments>
            <pubDate>Mon, 01 Jun 2009 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">2473806</guid>        </item>
        <item>
            <title>Gene loss under neighborhood selection following whole genome duplication and the reconstruction of the ancestral populus genome.</title>
            <link>http://www.medworm.com/index.php?rid=2473804&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19507287%26dopt%3DAbstract</link>
            <description>Authors: Zheng C, Kerr Wall P, Leebens-Mack J, DE Pamphilis C, Albert VA, Sankoff D
    We develop criteria to detect neighborhood selection effects on gene loss following whole genome duplication, and apply them to the recently sequenced poplar (Populus trichocarpa) genome. We improve on guided genome halving algorithms so that several thousand gene sets, each containing two paralogs in the descendant T of the doubling event and their single ortholog from an undoubled reference genome R, can be analyzed to reconstruct the ancestor A of T at the time of doubling. At the same time, large numbers of defective gene sets, either missing one paralog from T or missing their ortholog in R, may be incorporated into the analysis in a consistent way. We apply this genomic rearrangement distance-base...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2473804</comments>
            <pubDate>Mon, 01 Jun 2009 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">2473804</guid>        </item>
        <item>
            <title>An almost linear time algorithm for a general haplotype solution on tree pedigrees with no recombination and its extensions.</title>
            <link>http://www.medworm.com/index.php?rid=2473803&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19507288%26dopt%3DAbstract</link>
            <description>Authors: Li X, Li J
    We study the haplotype inference problem from pedigree data under the zero recombination assumption, which is well supported by real data for tightly linked markers (i.e. single nucleotide polymorphisms (SNPs)) over a relatively large chromosome segment. We solve the problem in a rigorous mathematical manner by formulating genotype constraints as a linear system of inheritance variables. We then utilize disjoint-set structures to encode connectivity information among individuals, to detect constraints from genotypes, and to check consistency of constraints. On a tree pedigree without missing data, our algorithm can output a general solution as well as the number of total specific solutions in a nearly linear time O(mn . alpha(n)), where m is the number of loci, n is...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2473803</comments>
            <pubDate>Mon, 01 Jun 2009 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">2473803</guid>        </item>
        <item>
            <title>Peak detection in mass spectrometry by gabor filters and envelope analysis.</title>
            <link>http://www.medworm.com/index.php?rid=2473802&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19507289%26dopt%3DAbstract</link>
            <description>Authors: Nguyen N, Huang H, Oraintara S, Vo A
    Mass Spectrometry (MS) is increasingly being used to discover diseases-related proteomic patterns. The peak detection step is one of the most important steps in the typical analysis of MS data. Recently, many new algorithms have been proposed to increase true position rate with low false discovery rate in peak detection. Most of them follow two approaches: one is the denoising approach and the other is the decomposing approach. In the previous studies, the decomposition of MS data method shows more potential than the first one. In this paper, we propose two novel methods, named GaborLocal and GaborEnvelop, both of which can detect more true peaks with a lower false discovery rate than previous methods. We employ the method of Gaussian local...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2473802</comments>
            <pubDate>Mon, 01 Jun 2009 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">2473802</guid>        </item>
        <item>
            <title>Iterative non-sequential protein structural alignment.</title>
            <link>http://www.medworm.com/index.php?rid=2473740&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19507290%26dopt%3DAbstract</link>
            <description>Authors: Salem S, Zaki MJ, Bystroff C
    Structural similarity between proteins gives us insights into their evolutionary relationships when there is low sequence similarity. In this paper, we present a novel approach called SNAP for non-sequential pair-wise structural alignment. Starting from an initial alignment, our approach iterates over a two-step process consisting of a superposition step and an alignment step, until convergence. We propose a novel greedy algorithm to construct both sequential and non-sequential alignments. The quality of SNAP alignments were assessed by comparing against the manually curated reference alignments in the challenging SISY and RIPC datasets. Moreover, when applied to a dataset of 4410 protein pairs selected from the CATH database, SNAP produced longer ...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2473740</comments>
            <pubDate>Mon, 01 Jun 2009 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">2473740</guid>        </item>
        <item>
            <title>Supervised ensembles of prediction methods for subcellular localization.</title>
            <link>http://www.medworm.com/index.php?rid=2473827&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19340915%26dopt%3DAbstract</link>
            <description>Authors: Assfalg J, Gong J, Kriegel HP, Pryakhin A, Wei T, Zimek A
    In the past decade, many automated prediction methods for the subcellular localization of proteins have been proposed, utilizing a wide range of principles and learning approaches. Based on an experimental evaluation of different methods and their theoretical properties, we propose to combine a well-balanced set of existing approaches to new, ensemble-based prediction methods. The experimental evaluation shows that our ensembles improve substantially over the underlying base methods.
    PMID: 19340915 [PubMed - in process] (Source: Journal of Bioinformatics and Computational Biology)</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
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            <pubDate>Wed, 01 Apr 2009 04:00:00 +0100</pubDate>
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        <item>
            <title>Alignment of minisatellite maps based on run-length encoding scheme.</title>
            <link>http://www.medworm.com/index.php?rid=2473825&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19340916%26dopt%3DAbstract</link>
            <description>Authors: Abouelhoda MI, Giegerich R, Behzadi B, Steyaert JM
    Subsequent duplication events are responsible for the evolution of the minisatellite maps. Alignment of two minisatellite maps should therefore take these duplication events into account, in addition to the well-known edit operations. All algorithms for computing an optimal alignment of two maps, including the one presented here, first deduce the costs of optimal duplication scenarios for all substrings of the given maps. Then, they incorporate the pre-computed costs in the alignment recurrence. However, all previous algorithms addressing this problem are dependent on the number of distinct map units (map alphabet) and do not fully make use of the repetitiveness of the map units. In this paper, we present an algorithm that rem...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2473825</comments>
            <pubDate>Wed, 01 Apr 2009 04:00:00 +0100</pubDate>
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        <item>
            <title>Automatic modeling of signaling pathways by network flow model.</title>
            <link>http://www.medworm.com/index.php?rid=2473823&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19340917%26dopt%3DAbstract</link>
            <description>Authors: Zhao XM, Wang RS, Chen L, Aihara K
    Signal transduction is an important process that controls cell proliferation, metabolism, differentiation, and so on. Effective computational models which unravel such a process by taking advantage of high-throughput genomic and proteomic data are highly demanded to understand the essential mechanisms underlying signal transduction. Since protein-protein interaction (PPI) plays an important role in signal transduction, in this paper, we present a novel method for modeling signaling pathways from PPI networks automatically. Given an undirected weighted protein interaction network, finding signaling pathways is treated as searching for optimal subnetworks according to some cost function. To cope with this optimization problem, a network flow mo...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
            <type>journals</type>
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            <pubDate>Wed, 01 Apr 2009 04:00:00 +0100</pubDate>
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            <title>Symbolic approaches for finding control strategies in Boolean Networks.</title>
            <link>http://www.medworm.com/index.php?rid=2473821&amp;cid=s_33199_79_f&amp;fid=33199&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19340918%26dopt%3DAbstract</link>
            <description>We present an exact algorithm, based on techniques from the field of Model Checking, for finding control policies for Boolean Networks (BN) with control nodes. Given a BN, a set of starting states, I, a set of goal states, F, and a target time, t, our algorithm automatically finds a sequence of control signals that deterministically drives the BN from I to F at, or before time t, or else guarantees that no such policy exists. Despite recent hardness-results for finding control policies for BNs, we show that, in practice, our algorithm runs in seconds to minutes on over 13,400 BNs of varying sizes and topologies, including a BN model of embryogenesis in Drosophila melanogaster with 15,360 Boolean variables. We then extend our method to automatically identify a set of Boolean transfer functi...</description>
            <author>Journal of Bioinformatics and Computational Biology</author>
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            <pubDate>Wed, 01 Apr 2009 04:00:00 +0100</pubDate>
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