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        <title>Briefings in Bioinformatics 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 'Briefings in Bioinformatics' source.</description>
        <link><![CDATA[http://www.medworm.com/rss/search.php?qu=Briefings+in+Bioinformatics&t=Briefings+in+Bioinformatics&s=Search&f=source]]></link>
        <lastBuildDate>Mon, 15 Mar 2010 16:49:25 +0100</lastBuildDate>
        <item>
            <title>GPU computing for systems biology.</title>
            <link>http://www.medworm.com/index.php?rid=3354918&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20211843%26dopt%3DAbstract</link>
            <description>Authors: Dematt&amp;#xE9; L, Prandi D
    The development of detailed, coherent, models of complex biological systems is recognized as a key requirement for integrating the increasing amount of experimental data. In addition, in-silico simulation of bio-chemical models provides an easy way to test different experimental conditions, helping in the discovery of the dynamics that regulate biological systems. However, the computational power required by these simulations often exceeds that available on common desktop computers and thus expensive high performance computing solutions are required. An emerging alternative is represented by general-purpose scientific computing on graphics processing units (GPGPU), which offers the power of a small computer cluster at a cost of approximately $400. Comp...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3354918</comments>
            <pubDate>Sun, 07 Mar 2010 00:00:00 +0100</pubDate>
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            <title>Ensemble learning algorithms for classification of mtDNA into haplogroups.</title>
            <link>http://www.medworm.com/index.php?rid=3340110&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20203074%26dopt%3DAbstract</link>
            <description>Authors: Wong C, Li Y, Lee C, Huang CH
    Classification of mitochondrial DNA (mtDNA) into their respective haplogroups allows the addressing of various anthropologic and forensic issues. Unique to mtDNA is its abundance and non-recombining uni-parental mode of inheritance; consequently, mutations are the only changes observed in the genetic material. These individual mutations are classified into their cladistic haplogroups allowing the tracing of different genetic branch points in human (and other organisms) evolution. Due to the large number of samples, it becomes necessary to automate the classification process. Using 5-fold cross-validation, we investigated two classification techniques on the consented database of 21 141 samples published by the Genographic project. The support vect...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3340110</comments>
            <pubDate>Thu, 04 Mar 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3340110</guid>        </item>
        <item>
            <title>Preprocessing and downstream analysis of microarray DNA copy number profiles.</title>
            <link>http://www.medworm.com/index.php?rid=3303182&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20172948%26dopt%3DAbstract</link>
            <description>Authors: van de Wiel MA, Picard F, van Wieringen WN, Ylstra B
    Analysis of DNA copy number profiles requires methods tailored to the specific nature of these data. The number of available data analysis methods has grown enormously in the last 5 years. We discuss the typical characteristics of DNA copy number data, as measured by microarray technology and review the extensive literature on preprocessing methods such as segmentation and calling. Subsequently, the focus narrows to applications of DNA copy number in cancer, in particular, several downstream analyses of multi-sample data sets such as testing, clustering and classification. Finally, we look ahead: what should we prepare for and which methodology-related topics may deserve attention in the near future?
    PMID: 20172948 [PubM...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3303182</comments>
            <pubDate>Fri, 19 Feb 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3303182</guid>        </item>
        <item>
            <title>DNA barcoding: a six-question tour to improve users' awareness about the method.</title>
            <link>http://www.medworm.com/index.php?rid=3276973&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20156987%26dopt%3DAbstract</link>
            <description>Authors: Casiraghi M, Labra M, Ferri E, Galimberti A, De Mattia F
    DNA barcoding is a recent and widely used molecular-based identification system that aims to identify biological specimens, and to assign them to a given species. However, DNA barcoding is even more than this, and besides many practical uses, it can be considered the core of an integrated taxonomic system, where bioinformatics plays a key role. DNA barcoding data could be interpreted in different ways depending on the examined taxa but the technique relies on standardized approaches, methods and analyses. The existing reference towards a common way to treat DNA barcoding data, analyses and results is the Barcode of Life Data Systems. However, the scientific community has produced in the recent years a number of alternati...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3276973</comments>
            <pubDate>Mon, 15 Feb 2010 00:00:00 +0100</pubDate>
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        <item>
            <title>Fast and efficient searching of biological data resources--using EB-eye.</title>
            <link>http://www.medworm.com/index.php?rid=3269972&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20150321%26dopt%3DAbstract</link>
            <description>Authors: Valentin F, Squizzato S, Goujon M, McWilliam H, Paern J, Lopez R
    The EB-eye is a fast and efficient search engine that provides easy and uniform access to the biological data resources hosted at the EMBL-EBI. Currently, users can access information from more than 62 distinct datasets covering some 400 million entries. The data resources represented in the EB-eye include: nucleotide and protein sequences at both the genomic and proteomic levels, structures ranging from chemicals to macro-molecular complexes, gene-expression experiments, binary level molecular interactions as well as reaction maps and pathway models, functional classifications, biological ontologies, and comprehensive literature libraries covering the biomedical sciences and related intellectual property. The EB...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3269972</comments>
            <pubDate>Thu, 11 Feb 2010 00:00:00 +0100</pubDate>
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            <title>High performance cellular level agent-based simulation with FLAME for the GPU.</title>
            <link>http://www.medworm.com/index.php?rid=3236789&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20123941%26dopt%3DAbstract</link>
            <description>Authors: Richmond P, Walker D, Coakley S, Romano D
    Driven by the availability of experimental data and ability to simulate a biological scale which is of immediate interest, the cellular scale is fast emerging as an ideal candidate for middle-out modelling. As with 'bottom-up' simulation approaches, cellular level simulations demand a high degree of computational power, which in large-scale simulations can only be achieved through parallel computing. The flexible large-scale agent modelling environment (FLAME) is a template driven framework for agent-based modelling (ABM) on parallel architectures ideally suited to the simulation of cellular systems. It is available for both high performance computing clusters (www.flame.ac.uk) and GPU hardware (www.flamegpu.com) and uses a formal spec...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3236789</comments>
            <pubDate>Mon, 01 Feb 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3236789</guid>        </item>
        <item>
            <title>Semiparametric prognosis models in genomic studies.</title>
            <link>http://www.medworm.com/index.php?rid=3236788&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20123942%26dopt%3DAbstract</link>
            <description>Authors: Ma S, Huang J, Shi M, Li Y, Shia BC
    Development of high-throughput technologies makes it possible to survey the whole genome. Genomic studies have been extensively conducted, searching for markers with predictive power for prognosis of complex diseases such as cancer, diabetes and obesity. Most existing statistical analyses are focused on developing marker selection techniques, while little attention is paid to the underlying prognosis models. In this article, we review three commonly used prognosis models, namely the Cox, additive risk and accelerated failure time models. We conduct simulation and show that gene identification can be unsatisfactory under model misspecification. We analyze three cancer prognosis studies under the three models, and show that the gene identifica...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3236788</comments>
            <pubDate>Mon, 01 Feb 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3236788</guid>        </item>
        <item>
            <title>Flexible experimentation in the modeling and simulation framework JAMES II--implications for computational systems biology.</title>
            <link>http://www.medworm.com/index.php?rid=3229833&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20118105%26dopt%3DAbstract</link>
            <description>Authors: Ewald R, Himmelspach J, Jeschke M, Leye S, Uhrmacher AM
    Dry-lab experimentation is being increasingly used to complement wet-lab experimentation. However, conducting dry-lab experiments is a challenging endeavor that requires the combination of diverse techniques. JAMES II, a plug-in-based open source modeling and simulation framework, facilitates the exploitation and configuration of these techniques. The different aspects that form an experiment are made explicit to facilitate repeatability and reuse. Each of those influences the performance and the quality of the simulation experiment. Common experimentation pitfalls and current challenges are discussed along the way.
    PMID: 20118105 [PubMed - as supplied by publisher] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3229833</comments>
            <pubDate>Thu, 28 Jan 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3229833</guid>        </item>
        <item>
            <title>Estimating the divisibility of complex biological networks by sparseness indices.</title>
            <link>http://www.medworm.com/index.php?rid=3172523&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20064873%26dopt%3DAbstract</link>
            <description>Authors: Mazza T, Romanel A, Jord&amp;#xE1;n F
    In order to understand the complex relationships among the components of biological systems, network models have been used for a long time. Although they have been extensively used for visualization, data storage, structural analysis and simulation, some computational processes are still very inefficient when applied on complex networks. In particular, any parallel simulation technique requires a network previously divided into a number of clusters in numbers equal to that of the available processors. At the same time, let maximally disconnected clusters be chosen in order to minimize extra-communication overhead and to optimize the overall computational efficiency. Obtaining such a disconnection becomes a computationally hard problem when dis...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3172523</comments>
            <pubDate>Mon, 11 Jan 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3172523</guid>        </item>
        <item>
            <title>Toward the dynamic interactome: it's about time.</title>
            <link>http://www.medworm.com/index.php?rid=3164483&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20061351%26dopt%3DAbstract</link>
            <description>Authors: Przytycka TM, Singh M, Slonim DK
    Dynamic molecular interactions play a central role in regulating the functioning of cells and organisms. The availability of experimentally determined large-scale cellular networks, along with other high-throughput experimental data sets that provide snapshots of biological systems at different times and conditions, is increasingly helpful in elucidating interaction dynamics. Here we review the beginnings of a new subfield within computational biology, one focused on the global inference and analysis of the dynamic interactome. This burgeoning research area, which entails a shift from static to dynamic network analysis, promises to be a major step forward in our ability to model and reason about cellular function and behavior.
    PMID: 2006135...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3164483</comments>
            <pubDate>Fri, 08 Jan 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3164483</guid>        </item>
        <item>
            <title>Real-time classification of datasets with hardware embedded neuromorphic neural networks.</title>
            <link>http://www.medworm.com/index.php?rid=3153991&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20053732%26dopt%3DAbstract</link>
            <description>This article demonstrates that artificial spiking neural networks-built to resemble the biological model-encoding information in the timing of single spikes, are capable of computing and learning clusters from realistic data. It shows how a spiking neural network based on spike-time coding can successfully perform unsupervised and supervised clustering on real-world data. A temporal encoding procedure of continuously valued data is developed, together with a hardware implementation oriented new learning rule set. Solutions that make use of embedded soft-core microcontrollers are investigated, to implement some of the most resource-consuming components of the artificial neural network. Details of the implementations are given, with benchmark application evaluation and test bench description...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3153991</comments>
            <pubDate>Wed, 06 Jan 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3153991</guid>        </item>
        <item>
            <title>Genome variation discovery with high-throughput sequencing data.</title>
            <link>http://www.medworm.com/index.php?rid=3153990&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20053733%26dopt%3DAbstract</link>
            <description>Authors: Dalca AV, Brudno M
    The advent of high-throughput sequencing (HTS) technologies is enabling sequencing of human genomes at a significantly lower cost. The availability of these genomes is hoped to enable novel medical diagnostics and treatment, specific to the individual, thus launching the era of personalized medicine. The data currently generated by HTS machines require extensive computational analysis in order to identify genomic variants present in the sequenced individual. In this paper, we overview HTS technologies and discuss several of the plethora of algorithms and tools designed to analyze HTS data, including algorithms for read mapping, as well as methods for identification of single-nucleotide polymorphisms, insertions/deletions and large-scale structural variants a...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3153990</comments>
            <pubDate>Wed, 06 Jan 2010 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3153990</guid>        </item>
        <item>
            <title>Molecular networks for the study of TCM Pharmacology.</title>
            <link>http://www.medworm.com/index.php?rid=3130105&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20038567%26dopt%3DAbstract</link>
            <description>Authors: Zhao J, Jiang P, Zhang W
    To target complex, multi-factorial diseases more effectively, there has been an emerging trend of multi-target drug development based on network biology, as well as an increasing interest in traditional Chinese medicine (TCM) that applies a more holistic treatment to diseases. Thousands of years' clinic practices in TCM have accumulated a considerable number of formulae that exhibit reliable in vivo efficacy and safety. However, the molecular mechanisms responsible for their therapeutic effectiveness are still unclear. The development of network-based systems biology has provided considerable support for the understanding of the holistic, complementary and synergic essence of TCM in the context of molecular networks. This review introduces available so...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3130105</comments>
            <pubDate>Mon, 28 Dec 2009 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3130105</guid>        </item>
        <item>
            <title>Simulation of P systems with active membranes on CUDA.</title>
            <link>http://www.medworm.com/index.php?rid=3130104&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20038568%26dopt%3DAbstract</link>
            <description>Authors: Cecilia JM, Garc&amp;#xED;a JM, Guerrero GD, Mart&amp;#xED;nez-Del-Amor MA, P&amp;#xE9;rez-Hurtado I, P&amp;#xE9;rez-Jim&amp;#xE9;nez MJ
    P systems or Membrane Systems provide a high-level computational modelling framework that combines the structure and dynamic aspects of biological systems in a relevant and understandable way. They are inherently parallel and non-deterministic computing devices. In this article, we discuss the motivation, design principles and key of the implementation of a simulator for the class of recognizer P systems with active membranes running on a (GPU). We compare our parallel simulator for GPUs to the simulator developed for a single central processing unit (CPU), showing that GPUs are better suited than CPUs to simulate P systems due to their highly parallel nature.
 ...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3130104</comments>
            <pubDate>Mon, 28 Dec 2009 00:00:00 +0100</pubDate>
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        <item>
            <title>Multi-scale modelling in computational biomedicine.</title>
            <link>http://www.medworm.com/index.php?rid=3119512&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20028713%26dopt%3DAbstract</link>
            <description>This article reviews the currently emerging field of multi-scale modelling in computational biomedicine. Many exciting multi-scale models exist or are under development. However, an underpinning multi-scale modelling methodology seems to be missing. We propose a direction that complements the classic dynamical systems approach and introduce two distinct case studies, transmission of resistance in human immunodeficiency virus spreading and in-stent restenosis in coronary artery disease.
    PMID: 20028713 [PubMed - as supplied by publisher] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3119512</comments>
            <pubDate>Tue, 22 Dec 2009 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3119512</guid>        </item>
        <item>
            <title>Dealing with missing values in large-scale studies: microarray data imputation and beyond.</title>
            <link>http://www.medworm.com/index.php?rid=3067513&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19965979%26dopt%3DAbstract</link>
            <description>Authors: Aittokallio T
    High-throughput biotechnologies, such as gene expression microarrays or mass-spectrometry-based proteomic assays, suffer from frequent missing values due to various experimental reasons. Since the missing data points can hinder downstream analyses, there exists a wide variety of ways in which to deal with missing values in large-scale data sets. Nowadays, it has become routine to estimate (or impute) the missing values prior to the actual data analysis. After nearly a decade since the publication of the first missing value imputation methods for gene expression microarray data, new imputation approaches are still being developed at an increasing rate. However, what is lagging behind is a systematic and objective evaluation of the strengths and weaknesses of the d...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3067513</comments>
            <pubDate>Fri, 04 Dec 2009 00:00:00 +0100</pubDate>
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        <item>
            <title>Detection of human interchromosomal trans-splicing in sequence databanks.</title>
            <link>http://www.medworm.com/index.php?rid=3057355&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19955235%26dopt%3DAbstract</link>
            <description>Authors: Herai RH, Yamagishi ME
    Trans-splicing is a common phenomenon in nematodes and kinetoplastids, and it has also been reported in other organisms, including humans. Up to now, all in silico strategies to find evidence of trans-splicing in humans have required that the candidate sequences follow the consensus splicing site rules (spliceosome-mediated mechanism). However, this criterion is not supported by the best human experimental evidence, which, except in a single case, do not follow canonical splicing sites. Moreover, recent findings describe a novel alternative tRNA mediated trans-splicing mechanism, which prescinds the spliceosome machinery. In order to answer the question, 'Are there hybrid mRNAs in sequence databanks, whose characteristics resemble those of the best human...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3057355</comments>
            <pubDate>Wed, 02 Dec 2009 00:00:00 +0100</pubDate>
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        <item>
            <title>Current progress in patient-specific modeling.</title>
            <link>http://www.medworm.com/index.php?rid=3057354&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19955236%26dopt%3DAbstract</link>
            <description>We present a survey of recent advancements in the emerging field of patient-specific modeling (PSM). Researchers in this field are currently simulating a wide variety of tissue and organ dynamics to address challenges in various clinical domains. The majority of this research employs three-dimensional, image-based modeling techniques. Recent PSM publications mostly represent feasibility or preliminary validation studies on modeling technologies, and these systems will require further clinical validation and usability testing before they can become a standard of care. We anticipate that with further testing and research, PSM-derived technologies will eventually become valuable, versatile clinical tools.
    PMID: 19955236 [PubMed - as supplied by publisher] (Source: Briefings in Bioinformat...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
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            <pubDate>Wed, 02 Dec 2009 00:00:00 +0100</pubDate>
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            <title>Pathway Tools version 13.0: integrated software for pathway/genome informatics and systems biology.</title>
            <link>http://www.medworm.com/index.php?rid=3057353&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19955237%26dopt%3DAbstract</link>
            <description>This article provides an overview of Pathway Tools capabilities. The software performs multiple computational inferences including prediction of metabolic pathways, prediction of metabolic pathway hole fillers and prediction of operons. It enables interactive editing of PGDBs by DB curators. It supports web publishing of PGDBs, and provides a large number of query and visualization tools. The software also supports comparative analyses of PGDBs, and provides several systems biology analyses of PGDBs including reachability analysis of metabolic networks, and interactive tracing of metabolites through a metabolic network. More than 800 PGDBs have been created using Pathway Tools by scientists around the world, many of which are curated DBs for important model organisms. Those PGDBs can be ex...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3057353</comments>
            <pubDate>Wed, 02 Dec 2009 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3057353</guid>        </item>
        <item>
            <title>BioModels.net Web Services, a free and integrated toolkit for computational modelling software.</title>
            <link>http://www.medworm.com/index.php?rid=3033883&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19939940%26dopt%3DAbstract</link>
            <description>Authors: Li C, Courtot M, Le Nov&amp;#xE8;re N, Laibe C
    Exchanging and sharing scientific results are essential for researchers in the field of computational modelling. BioModels.net defines agreed-upon standards for model curation. A fundamental one, MIRIAM (Minimum Information Requested in the Annotation of Models), standardises the annotation and curation process of quantitative models in biology. To support this standard, MIRIAM Resources maintains a set of standard data types for annotating models, and provides services for manipulating these annotations. Furthermore, BioModels.net creates controlled vocabularies, such as SBO (Systems Biology Ontology) which strictly indexes, defines and links terms used in Systems Biology. Finally, BioModels Database provides a free, centralised, pub...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3033883</comments>
            <pubDate>Wed, 25 Nov 2009 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3033883</guid>        </item>
        <item>
            <title>Detection call algorithms for high-throughput gene expression microarray data.</title>
            <link>http://www.medworm.com/index.php?rid=3033882&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19939941%26dopt%3DAbstract</link>
            <description>We examined the performance of these detection call algorithms and default parameters by applying the methods to two spike-in datasets. We show that the default parameters for qualitative detection calls yield few absent calls for high spike-in concentrations. When genes of interest are expected to be present at very low concentrations, spike-in datasets can be useful for appropriately adjusting the tuning parameters for qualitative detection calls.
    PMID: 19939941 [PubMed - as supplied by publisher] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=3033882</comments>
            <pubDate>Wed, 25 Nov 2009 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">3033882</guid>        </item>
        <item>
            <title>The challenges of informatics in synthetic biology: from biomolecular networks to artificial organisms.</title>
            <link>http://www.medworm.com/index.php?rid=2992897&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19906839%26dopt%3DAbstract</link>
            <description>Authors: Alterovitz G, Muso T, Ramoni MF
    The field of synthetic biology holds an inspiring vision for the future; it integrates computational analysis, biological data and the systems engineering paradigm in the design of new biological machines and systems. These biological machines are built from basic biomolecular components analogous to electrical devices, and the information flow among these components requires the augmentation of biological insight with the power of a formal approach to information management. Here we review the informatics challenges in synthetic biology along three dimensions: in silico, in vitro and in vivo. First, we describe state of the art of the in silico support of synthetic biology, from the specific data exchange formats, to the most popular software p...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2992897</comments>
            <pubDate>Wed, 11 Nov 2009 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">2992897</guid>        </item>
        <item>
            <title>Bioinformatics approaches for genomics and post genomics applications of next-generation sequencing.</title>
            <link>http://www.medworm.com/index.php?rid=2944377&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19864250%26dopt%3DAbstract</link>
            <description>Authors: Horner DS, Pavesi G, Castrignan&amp;#xF2; T, De Meo PD, Liuni S, Sammeth M, Picardi E, Pesole G
    Technical advances such as the development of molecular cloning, Sanger sequencing, PCR and oligonucleotide microarrays are key to our current capacity to sequence, annotate and study complete organismal genomes. Recent years have seen the development of a variety of so-called 'next-generation' sequencing platforms, with several others anticipated to become available shortly. The previously unimaginable scale and economy of these methods, coupled with their enthusiastic uptake by the scientific community and the potential for further improvements in accuracy and read length, suggest that these technologies are destined to make a huge and ongoing impact upon genomic and post-genomic biol...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2944377</comments>
            <pubDate>Tue, 27 Oct 2009 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">2944377</guid>        </item>
        <item>
            <title>Knowledge-based data analysis comes of age.</title>
            <link>http://www.medworm.com/index.php?rid=2935549&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19854753%26dopt%3DAbstract</link>
            <description>Authors: Ochs MF
    The emergence of high-throughput technologies for measuring biological systems has introduced problems for data interpretation that must be addressed for proper inference. First, analysis techniques need to be matched to the biological system, reflecting in their mathematical structure the underlying behavior being studied. When this is not done, mathematical techniques will generate answers, but the values and reliability estimates may not accurately reflect the biology. Second, analysis approaches must address the vast excess in variables measured (e.g. transcript levels of genes) over the number of samples (e.g. tumors, time points), known as the 'large-p, small-n' problem. In large-p, small-n paradigms, standard statistical techniques generally fail, and computatio...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2935549</comments>
            <pubDate>Fri, 23 Oct 2009 00:00:00 +0100</pubDate>
            <guid isPermaLink="false">2935549</guid>        </item>
        <item>
            <title>Gene association analysis: a survey of frequent pattern mining from gene expression data.</title>
            <link>http://www.medworm.com/index.php?rid=2877329&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19815645%26dopt%3DAbstract</link>
            <description>Authors: Alves R, Rodriguez-Baena DS, Aguilar-Ruiz JS
    Establishing an association between variables is always of interest in genomic studies. Generation of DNA microarray gene expression data introduces a variety of data analysis issues not encountered in traditional molecular biology or medicine. Frequent pattern mining (FPM) has been applied successfully in business and scientific data for discovering interesting association patterns, and is becoming a promising strategy in microarray gene expression analysis. We review the most relevant FPM strategies, as well as surrounding main issues when devising efficient and practical methods for gene association analysis (GAA). We observed that, so far, scalability achieved by efficient methods does not imply biological soundness of the disco...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2877329</comments>
            <pubDate>Wed, 07 Oct 2009 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">2877329</guid>        </item>
        <item>
            <title>Advances in metaheuristics for gene selection and classification of microarray data.</title>
            <link>http://www.medworm.com/index.php?rid=2856111&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19789265%26dopt%3DAbstract</link>
            <description>Authors: Duval B, Hao JK
    Gene selection aims at identifying a (small) subset of informative genes from the initial data in order to obtain high predictive accuracy for classification. Gene selection can be considered as a combinatorial search problem and thus be conveniently handled with optimization methods. In this article, we summarize some recent developments of using metaheuristic-based methods within an embedded approach for gene selection. In particular, we put forward the importance and usefulness of integrating problem-specific knowledge into the search operators of such a method. To illustrate the point, we explain how ranking coefficients of a linear classifier such as support vector machine (SVM) can be profitably used to reinforce the search efficiency of Local Search and ...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2856111</comments>
            <pubDate>Mon, 28 Sep 2009 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">2856111</guid>        </item>
        <item>
            <title>Bioinformatics in the orphan crops.</title>
            <link>http://www.medworm.com/index.php?rid=2775297&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19734255%26dopt%3DAbstract</link>
            <description>Authors: Armstead I, Huang L, Ravagnani A, Robson P, Ougham H
    Orphan crops are those which are grown as food, animal feed or other crops of some importance in agriculture, but which have not yet received the investment of research effort or funding required to develop significant public bioinformatics resources. Where an orphan crop is related to a well-characterised model plant species, comparative genomics and bioinformatics can often, though not always, be exploited to assist research and crop improvement. This review addresses some challenges and opportunities presented by bioinformatics in the orphan crops, using three examples: forage grasses from the genera Lolium and Festuca, forage legumes and the second generation energy crop Miscanthus.
    PMID: 19734255 [PubMed - as suppli...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2775297</comments>
            <pubDate>Thu, 03 Sep 2009 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">2775297</guid>        </item>
        <item>
            <title>Stability and aggregation of ranked gene lists.</title>
            <link>http://www.medworm.com/index.php?rid=2703206&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19679825%26dopt%3DAbstract</link>
            <description>Authors: Boulesteix AL, Slawski M
    Ranked gene lists are highly instable in the sense that similar measures of differential gene expression may yield very different rankings, and that a small change of the data set usually affects the obtained gene list considerably. Stability issues have long been under-considered in the literature, but they have grown to a hot topic in the last few years, perhaps as a consequence of the increasing skepticism on the reproducibility and clinical applicability of molecular research findings. In this article, we review existing approaches for the assessment of stability of ranked gene lists and the related problem of aggregation, give some practical recommendations, and warn against potential misuse of these methods. This overview is illustrated through a...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2703206</comments>
            <pubDate>Sun, 16 Aug 2009 08:12:04 +0100</pubDate>
            <guid isPermaLink="false">2703206</guid>        </item>
        <item>
            <title>Biological knowledge management: the emerging role of the Semantic Web technologies.</title>
            <link>http://www.medworm.com/index.php?rid=2473126&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19457869%26dopt%3DAbstract</link>
            <description>Authors: Antezana E, Kuiper M, Mironov V
    New knowledge is produced at a continuously increasing speed, and the list of papers, databases and other knowledge sources that a researcher in the life sciences needs to cope with is actually turning into a problem rather than an asset. The adequate management of knowledge is therefore becoming fundamentally important for life scientists, especially if they work with approaches that thoroughly depend on knowledge integration, such as systems biology. Several initiatives to organize biological knowledge sources into a readily exploitable resourceome are presently being carried out. Ontologies and Semantic Web technologies revolutionize these efforts. Here, we review the benefits, trends, current possibilities, and the potential this holds for t...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2473126</comments>
            <pubDate>Sat, 13 Jun 2009 15:19:55 +0100</pubDate>
            <guid isPermaLink="false">2473126</guid>        </item>
        <item>
            <title>Genome assembly reborn: recent computational challenges.</title>
            <link>http://www.medworm.com/index.php?rid=2473124&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19482960%26dopt%3DAbstract</link>
            <description>Authors: Pop M
    Research into genome assembly algorithms has experienced a resurgence due to new challenges created by the development of next generation sequencing technologies. Several genome assemblers have been published in recent years specifically targeted at the new sequence data; however, the ever-changing technological landscape leads to the need for continued research. In addition, the low cost of next generation sequencing data has led to an increased use of sequencing in new settings. For example, the new field of metagenomics relies on large-scale sequencing of entire microbial communities instead of isolate genomes, leading to new computational challenges. In this article, we outline the major algorithmic approaches for genome assembly and describe recent developments in t...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2473124</comments>
            <pubDate>Sat, 13 Jun 2009 15:19:42 +0100</pubDate>
            <guid isPermaLink="false">2473124</guid>        </item>
        <item>
            <title>Briefings in bioinformatics.</title>
            <link>http://www.medworm.com/index.php?rid=2473120&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19505887%26dopt%3DAbstract</link>
            <description>Authors: Dubitzky W
    
    PMID: 19505887 [PubMed - in process] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2473120</comments>
            <pubDate>Sat, 13 Jun 2009 15:14:06 +0100</pubDate>
            <guid isPermaLink="false">2473120</guid>        </item>
        <item>
            <title>Approaches to neuroscience data integration.</title>
            <link>http://www.medworm.com/index.php?rid=2473096&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19505888%26dopt%3DAbstract</link>
            <description>Authors: Cheung KH, Lim E, Samwald M, Chen H, Marenco L, Holford ME, Morse TM, Mutalik P, Shepherd GM, Miller PL
    As the number of neuroscience databases increases, the need for neuroscience data integration grows. This paper reviews and compares several approaches, including the Neuroscience Database Gateway (NDG), Neuroscience Information Framework (NIF) and Entrez Neuron, which enable neuroscience database annotation and integration. These approaches cover a range of activities spanning from registry, discovery and integration of a wide variety of neuroscience data sources. They also provide different user interfaces for browsing, querying and displaying query results. In Entrez Neuron, for example, four different facets or tree views (neuron, neuronal property, gene and drug) are us...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2473096</comments>
            <pubDate>Sat, 13 Jun 2009 14:46:15 +0100</pubDate>
            <guid isPermaLink="false">2473096</guid>        </item>
        <item>
            <title>Computational methods for discovering gene networks from expression data.</title>
            <link>http://www.medworm.com/index.php?rid=2473094&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19505889%26dopt%3DAbstract</link>
            <description>Authors: Lee WP, Tzou WS
    Designing and conducting experiments are routine practices for modern biologists. The real challenge, especially in the post-genome era, usually comes not from acquiring data, but from subsequent activities such as data processing, analysis, knowledge generation and gaining insight into the research question of interest. The approach of inferring gene regulatory networks (GRNs) has been flourishing for many years, and new methods from mathematics, information science, engineering and social sciences have been applied. We review different kinds of computational methods biologists use to infer networks of varying levels of accuracy and complexity. The primary concern of biologists is how to translate the inferred network into hypotheses that can be tested with re...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2473094</comments>
            <pubDate>Sat, 13 Jun 2009 14:22:00 +0100</pubDate>
            <guid isPermaLink="false">2473094</guid>        </item>
        <item>
            <title>Computational methods for the detection of cis-regulatory modules.</title>
            <link>http://www.medworm.com/index.php?rid=2473122&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19498042%26dopt%3DAbstract</link>
            <description>Authors: Loo PV, Marynen P
    Metazoan transcription regulation occurs through the concerted action of multiple transcription factors that bind co-operatively to cis-regulatory modules (CRMs). The annotation of these key regulators of transcription is lagging far behind the annotation of the transcriptome itself. Here, we give an overview of existing computational methods to detect these CRMs in metazoan genomes. We subdivide these methods into three classes: CRM scanners screen sequences for CRMs based on predefined models that often consist of multiple position weight matrices (PWMs). CRM builders construct models of similar CRMs controlling a set of co-regulated or co-expressed genes. CRM genome screeners screen sequences or complete genomes for CRMs as homotypic or heterotypic cluster...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2473122</comments>
            <pubDate>Thu, 04 Jun 2009 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">2473122</guid>        </item>
        <item>
            <title>Recent advances in computer-aided drug design.</title>
            <link>http://www.medworm.com/index.php?rid=2473128&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19433475%26dopt%3DAbstract</link>
            <description>Authors: Song CM, Lim SJ, Tong JC
    Modern drug discovery is characterized by the production of vast quantities of compounds and the need to examine these huge libraries in short periods of time. The need to store, manage and analyze these rapidly increasing resources has given rise to the field known as computer-aided drug design (CADD). CADD represents computational methods and resources that are used to facilitate the design and discovery of new therapeutic solutions. Digital repositories, containing detailed information on drugs and other useful compounds, are goldmines for the study of chemical reactions capabilities. Design libraries, with the potential to generate molecular variants in their entirety, allow the selection and sampling of chemical compounds with diverse characterist...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2473128</comments>
            <pubDate>Mon, 11 May 2009 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">2473128</guid>        </item>
        <item>
            <title>2D molecular graphics: a flattened world of chemistry and biology.</title>
            <link>http://www.medworm.com/index.php?rid=2473142&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19332474%26dopt%3DAbstract</link>
            <description>Authors: Zhou P, Shang Z
    Molecular graphics provides an intuitive way for representation, modeling and analysis of complex chemical and biological systems. It is now widely used in the theoretical chemistry, structural biology, molecular modeling and drug design communities. Traditional molecular graphics techniques mainly dedicate to showing molecular architectures at three-dimensional (3D) level. However, in some occasions the two-dimensional (2D) representation of molecular configurations, profiles, behaviors and interactions may be more readily acceptable for audiences, especially when we need to describe abstract information in a straightforward way or to present numerous data in schematic diagrams. In recent years, 2D representation methods/tools have been developed rapidly for v...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2473142</comments>
            <pubDate>Fri, 01 May 2009 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">2473142</guid>        </item>
        <item>
            <title>Taming the complexity of biological pathways through parallel computing.</title>
            <link>http://www.medworm.com/index.php?rid=2473140&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19339382%26dopt%3DAbstract</link>
            <description>Authors: Ballarini P, Guido R, Mazza T, Prandi D
    Biological systems are characterised by a large number of interacting entities whose dynamics is described by a number of reaction equations. Mathematical methods for modelling biological systems are mostly based on a centralised solution approach: the modelled system is described as a whole and the solution technique, normally the integration of a system of ordinary differential equations (ODEs) or the simulation of a stochastic model, is commonly computed in a centralised fashion. In recent times, research efforts moved towards the definition of parallel/distributed algorithms as a means to tackle the complexity of biological models analysis. In this article, we present a survey on the progresses of such parallelisation efforts describ...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2473140</comments>
            <pubDate>Fri, 01 May 2009 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">2473140</guid>        </item>
        <item>
            <title>Progress and challenges in predicting protein-protein interaction sites.</title>
            <link>http://www.medworm.com/index.php?rid=2473136&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19346321%26dopt%3DAbstract</link>
            <description>Authors: Ezkurdia I, Bartoli L, Fariselli P, Casadio R, Valencia A, Tress ML
    The identification of protein-protein interaction sites is an essential intermediate step for mutant design and the prediction of protein networks. In recent years a significant number of methods have been developed to predict these interface residues and here we review the current status of the field. Progress in this area requires a clear view of the methodology applied, the data sets used for training and testing the systems, and the evaluation procedures. We have analysed the impact of a representative set of features and algorithms and highlighted the problems inherent in generating reliable protein data sets and in the posterior analysis of the results. Although it is clear that there have been some impr...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2473136</comments>
            <pubDate>Fri, 01 May 2009 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">2473136</guid>        </item>
        <item>
            <title>Probes containing runs of guanines provide insights into the biophysics and bioinformatics of Affymetrix GeneChips.</title>
            <link>http://www.medworm.com/index.php?rid=2473134&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19359259%26dopt%3DAbstract</link>
            <description>Authors: Langdon WB, Upton GJ, Harrison AP
    The reliable interpretation of Affymetrix GeneChip data is a multi-faceted problem. The interplay between biophysics, bioinformatics and mining of GeneChip surveys is leading to new insights into how best to analyse the data. Many of the molecular processes occurring on the surfaces of GeneChips result from the high surface density of probes. Interactions between neighbouring adjacent probes affect their rate and strength of hybridization to targets. Competing targets may hybridize to the same probe, and targets may partially bind to more than one probe. The formation of these partial hybrids results in a number of probes not reaching thermodynamic equilibrium during hybridization. Moreover, some targets fold up, or cross-hybridize to other ta...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2473134</comments>
            <pubDate>Fri, 01 May 2009 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">2473134</guid>        </item>
        <item>
            <title>ImmunoGrid, an integrative environment for large-scale simulation of the immune system for vaccine discovery, design and optimization.</title>
            <link>http://www.medworm.com/index.php?rid=2473130&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19383844%26dopt%3DAbstract</link>
            <description>Authors: Pappalardo F, Halling-Brown MD, Rapin N, Zhang P, Alemani D, Emerson A, Paci P, Duroux P, Pennisi M, Palladini A, Miotto O, Churchill D, Rossi E, Shepherd AJ, Moss DS, Castiglione F, Bernaschi M, Lefranc MP, Brunak S, Motta S, Lollini PL, Basford KE, Brusic V
    Vaccine research is a combinatorial science requiring computational analysis of vaccine components, formulations and optimization. We have developed a framework that combines computational tools for the study of immune function and vaccine development. This framework, named ImmunoGrid combines conceptual models of the immune system, models of antigen processing and presentation, system-level models of the immune system, Grid computing, and database technology to facilitate discovery, formulation and optimization of vaccin...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2473130</comments>
            <pubDate>Fri, 01 May 2009 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">2473130</guid>        </item>
        <item>
            <title>An Ariadne's thread to the identification and annotation of noncoding RNAs in eukaryotes.</title>
            <link>http://www.medworm.com/index.php?rid=2473132&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19383843%26dopt%3DAbstract</link>
            <description>Authors: Sold&amp;#xE0; G, Makunin IV, Sezerman OU, Corradin A, Corti G, Guffanti A
    Non-protein coding RNAs (ncRNAs) have emerged as a vast and heterogeneous portion of eukaryotic transcriptomes. Several ncRNA families, either short (&amp;lt;200 nucleotides, nt) or long (&amp;gt;200 nt), have been described and implicated in a variety of biological processes, from translation to gene expression regulation and nuclear trafficking. Most probably, other families are still to be discovered. Computational methods for ncRNA research require different approaches from the ones normally used in the prediction of protein-coding genes. Indeed, primary sequence alone is often insufficient to infer ncRNA functionality, whereas secondary structure and local conservation of portions of the transcript could provi...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2473132</comments>
            <pubDate>Tue, 21 Apr 2009 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">2473132</guid>        </item>
        <item>
            <title>Development of biomarker classifiers from high-dimensional data.</title>
            <link>http://www.medworm.com/index.php?rid=2473138&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19346320%26dopt%3DAbstract</link>
            <description>This article reviews and evaluates some important aspects and key issues in the development of biomarker classifiers. Development of a biomarker classifier for high-throughput data involves two components: (i) model building and (ii) performance assessment. This article focuses on feature selection in model building and cross validation for performance assessment. A 'frequency' approach to feature selection is presented and compared to the 'conventional' approach in terms of the predictive accuracy and stability of the selected feature set. The two approaches are compared based on four biomarker classifiers, each with a different feature selection method and well-known classification algorithm. In each of the four classifiers the feature predictor set selected by the frequency approach is ...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2473138</comments>
            <pubDate>Fri, 03 Apr 2009 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">2473138</guid>        </item>
        <item>
            <title>Expression profiling of microRNAs by deep sequencing.</title>
            <link>http://www.medworm.com/index.php?rid=2473144&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19332473%26dopt%3DAbstract</link>
            <description>Authors: Creighton CJ, Reid JG, Gunaratne PH
    MicroRNAs are short non-coding RNAs that regulate the stability and translation of mRNAs. Profiling experiments, using microarray or deep sequencing technology, have identified microRNAs that are preferentially expressed in certain tissues, specific stages of development, or disease states such as cancer. Deep sequencing utilizes massively parallel sequencing, generating millions of small RNA sequence reads from a given sample. Profiling of microRNAs by deep sequencing measures absolute abundance and allows for the discovery of novel microRNAs that have eluded previous cloning and standard sequencing efforts. Public databases provide in silico predictions of microRNA gene targets by various algorithms. To better determine which of these pred...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2473144</comments>
            <pubDate>Mon, 30 Mar 2009 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">2473144</guid>        </item>
        <item>
            <title>FINDSITE: a combined evolution/structure-based approach to protein function prediction.</title>
            <link>http://www.medworm.com/index.php?rid=2297398&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19324930%26dopt%3DAbstract</link>
            <description>Authors: Skolnick J, Brylinski M
    A key challenge of the post-genomic era is the identification of the function(s) of all the molecules in a given organism. Here, we review the status of sequence and structure-based approaches to protein function inference and ligand screening that can provide functional insights for a significant fraction of the approximately 50% of ORFs of unassigned function in an average proteome. We then describe FINDSITE, a recently developed algorithm for ligand binding site prediction, ligand screening and molecular function prediction, which is based on binding site conservation across evolutionary distant proteins identified by threading. Importantly, FINDSITE gives comparable results when high-resolution experimental structures as well as predicted protein mo...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2297398</comments>
            <pubDate>Thu, 26 Mar 2009 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">2297398</guid>        </item>
        <item>
            <title>An introduction to artificial neural networks in bioinformatics--application to complex microarray and mass spectrometry datasets in cancer studies.</title>
            <link>http://www.medworm.com/index.php?rid=2297401&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19307287%26dopt%3DAbstract</link>
            <description>Authors: Lancashire LJ, Lemetre C, Ball GR
    Applications of genomic and proteomic technologies have seen a major increase, resulting in an explosion in the amount of highly dimensional and complex data being generated. Subsequently this has increased the effort by the bioinformatics community to develop novel computational approaches that allow for meaningful information to be extracted. This information must be of biological relevance and thus correlate to disease phenotypes of interest. Artificial neural networks are a form of machine learning from the field of artificial intelligence with proven pattern recognition capabilities and have been utilized in many areas of bioinformatics. This is due to their ability to cope with highly dimensional complex datasets such as those developed ...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2297401</comments>
            <pubDate>Mon, 23 Mar 2009 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">2297401</guid>        </item>
        <item>
            <title>The virtual cell--a candidate co-ordinator for 'middle-out' modelling of biological systems.</title>
            <link>http://www.medworm.com/index.php?rid=2284260&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19293250%26dopt%3DAbstract</link>
            <description>Authors: Walker DC, Southgate J
    Understanding the functioning of biological systems depends on tackling complexity spanning spatial scales from genome to organ to whole organism. The basic unit of life, the cell, acts to co-ordinate information received across these scales and processes the myriad of signals to produce an integrated cellular response. Cells interact with and respond to other cells through direct or indirect contact, resulting in emergent structure and function of tissues and organs. Systems biology has traditionally used either a 'top-down' or 'bottom-up' approach. However, neither approach takes account of heterogeneity or 'noise', which is an inherent feature of cellular behaviour and may have significant impact on system level behaviour. We review existing approache...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2284260</comments>
            <pubDate>Tue, 17 Mar 2009 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">2284260</guid>        </item>
        <item>
            <title>Flux balance analysis of biological systems: applications and challenges.</title>
            <link>http://www.medworm.com/index.php?rid=2274219&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19287049%26dopt%3DAbstract</link>
            <description>This article reviews the usefulness of FBA as a tool for gaining biological insights, advances in methodology enabling integration of regulatory information and thermodynamic constraints, and finally addresses the challenges that lie ahead. Various use scenarios and biological insights obtained from FBA, and applications in fields such metabolic engineering and drug target identification, are also discussed. Genome-scale constraint-based models have an immense potential for building and testing hypotheses, as well as to guide experimentation.
    PMID: 19287049 [PubMed - as supplied by publisher] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2274219</comments>
            <pubDate>Sun, 15 Mar 2009 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">2274219</guid>        </item>
        <item>
            <title>Life sciences on the Semantic Web: the Neurocommons and beyond.</title>
            <link>http://www.medworm.com/index.php?rid=2267690&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19282504%26dopt%3DAbstract</link>
            <description>We present the Neurocommons prototype knowledge base, a demonstration intended to show the feasibility and benefits of using these technologies. The prototype knowledge base can be used to experiment with and assess the scalability of current tools and methods for creating such a resource, and to elicit issues that will need to be addressed in order to expand the scope and use of it. We demonstrate the utility of the knowledge base by reviewing a few example queries that provide answers to precise questions relevant to the understanding of disease. All components of the knowledge base are freely available at http://neurocommons.org/, enabling readers to reconstruct the knowledge base and experiment with this new technology.
    PMID: 19282504 [PubMed - as supplied by publisher] (Source: Br...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2267690</comments>
            <pubDate>Thu, 12 Mar 2009 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">2267690</guid>        </item>
        <item>
            <title>Potential Bias in Go::TermFinder.</title>
            <link>http://www.medworm.com/index.php?rid=2259968&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19279157%26dopt%3DAbstract</link>
            <description>Authors: Flight RM, Wentzell PD
    The increased need for multiple statistical comparisons under conditions of non-independence in bioinformatics applications, such as DNA microarray data analysis, has led to the development of alternatives to the conventional Bonferroni correction for adjusting P-values. The use of the false discovery rate (FDR), in particular, has grown considerably. However, the calculation of the FDR frequently depends on drawing random samples from a population, and inappropriate sampling will result in a bias in the calculated FDR. In this work, we demonstrate a bias due to incorrect random sampling in the widely used GO::TermFinder package. Both T(2) and permutation tests are used to confirm the bias for a test set of data, which leads to an overestimation of the F...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2259968</comments>
            <pubDate>Wed, 11 Mar 2009 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">2259968</guid>        </item>
        <item>
            <title>Computational biology for cardiovascular biomarker discovery.</title>
            <link>http://www.medworm.com/index.php?rid=2259973&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19276200%26dopt%3DAbstract</link>
            <description>This article introduces key computational approaches and applications to biomarker discovery based on different types of 'omic' data. Although we emphasize applications in cardiovascular research, the computational requirements and advances discussed here are also relevant to other domains. We will start by introducing some of the contributions of computational biology to translational research, followed by an overview of methods and technologies used for the identification of biomarkers with predictive or classification value. The main types of 'omic' approaches to biomarker discovery will be presented with specific examples from cardiovascular research. This will include a review of computational methodologies for single-source and integrative data applications. Major computational metho...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2259973</comments>
            <pubDate>Tue, 10 Mar 2009 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">2259973</guid>        </item>
        <item>
            <title>Exploring autonomy through computational biomodelling.</title>
            <link>http://www.medworm.com/index.php?rid=2259970&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19276201%26dopt%3DAbstract</link>
            <description>Authors: Palfreyman N
    The question of whether living organisms possess autonomy of action is tied up with the nature of causal efficacy. Yet the nature of organisms is such that they frequently defy conventional causal language. Did the fig wasp select the fig, or vice versa? Is this an epithelial cell because of its genetic structure, or because it develops within the epithelium? The intimate coupling of biological levels of organisation leads developmental systems theory to deconstruct the biological organism into a life-cycle process which constitutes itself from the resources available within a complete developmental system. This radical proposal necessarily raises questions regarding the ontological status of organisms: Does an organism possess existence distinguishable from its m...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2259970</comments>
            <pubDate>Tue, 10 Mar 2009 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">2259970</guid>        </item>
        <item>
            <title>Computational systems biology of the cell cycle.</title>
            <link>http://www.medworm.com/index.php?rid=2259975&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19270018%26dopt%3DAbstract</link>
            <description>Authors: Csik&amp;#xE1;sz-Nagy A
    One of the early success stories of computational systems biology was the work done on cell-cycle regulation. The earliest mathematical descriptions of cell-cycle control evolved into very complex, detailed computational models that describe the regulation of cell division in many different cell types. On the way these models predicted several dynamical properties and unknown components of the system that were later experimentally verified/identified. Still, research on this field is far from over. We need to understand how the core cell-cycle machinery is controlled by internal and external signals, also in yeast cells and in the more complex regulatory networks of higher eukaryotes. Furthermore, there are many computational challenges what we face as new ...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2259975</comments>
            <pubDate>Fri, 06 Mar 2009 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">2259975</guid>        </item>
        <item>
            <title>A survey of available tools and web servers for analysis of protein-protein interactions and interfaces.</title>
            <link>http://www.medworm.com/index.php?rid=2218322&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19240123%26dopt%3DAbstract</link>
            <description>Authors: Tuncbag N, Kar G, Keskin O, Gursoy A, Nussinov R
    The unanimous agreement that cellular processes are (largely) governed by interactions between proteins has led to enormous community efforts culminating in overwhelming information relating to these proteins; to the regulation of their interactions, to the way in which they interact and to the function which is determined by these interactions. These data have been organized in databases and servers. However, to make these really useful, it is essential not only to be aware of these, but in particular to have a working knowledge of which tools to use for a given problem; what are the tool advantages and drawbacks; and no less important how to combine these for a particular goal since usually it is not one tool, but some combina...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2218322</comments>
            <pubDate>Tue, 24 Feb 2009 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">2218322</guid>        </item>
        <item>
            <title>A roadmap of clustering algorithms: finding a match for a biomedical application.</title>
            <link>http://www.medworm.com/index.php?rid=2218321&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19240124%26dopt%3DAbstract</link>
            <description>Authors: Andreopoulos B, An A, Wang X, Schroeder M
    Clustering is ubiquitously applied in bioinformatics with hierarchical clustering and k-means partitioning being the most popular methods. Numerous improvements of these two clustering methods have been introduced, as well as completely different approaches such as grid-based, density-based and model-based clustering. For improved bioinformatics analysis of data, it is important to match clusterings to the requirements of a biomedical application. In this article, we present a set of desirable clustering features that are used as evaluation criteria for clustering algorithms. We review 40 different clustering algorithms of all approaches and datatypes. We compare algorithms on the basis of desirable clustering features, and outline alg...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2218321</comments>
            <pubDate>Tue, 24 Feb 2009 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">2218321</guid>        </item>
        <item>
            <title>Towards pharmacogenomics knowledge discovery with the semantic web.</title>
            <link>http://www.medworm.com/index.php?rid=2218320&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19240125%26dopt%3DAbstract</link>
            <description>Authors: Dumontier M, Villanueva-Rosales N
    Pharmacogenomics aims to understand pharmacological response with respect to genetic variation. Essential to the delivery of better health care is the use of pharmacogenomics knowledge to answer questions about therapeutic, pharmacological or genetic aspects. Several XML markup languages have been developed to capture pharmacogenomic and related information so as to facilitate data sharing. However, recent advances in semantic web technologies have presented exciting new opportunities for pharmacogenomics knowledge discovery by representing the information with machine understandable semantics. Progress in this area is illustrated with reference to the personalized medicine project that aims to facilitate pharmacogenomics knowledge discovery t...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2218320</comments>
            <pubDate>Tue, 24 Feb 2009 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">2218320</guid>        </item>
        <item>
            <title>Biochemical simulations: stochastic, approximate stochastic and hybrid approaches.</title>
            <link>http://www.medworm.com/index.php?rid=2117181&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19151097%26dopt%3DAbstract</link>
            <description>Authors: Pahle J
    Computer simulations have become an invaluable tool to study the sometimes counterintuitive temporal dynamics of (bio-)chemical systems. In particular, stochastic simulation methods have attracted increasing interest recently. In contrast to the well-known deterministic approach based on ordinary differential equations, they can capture effects that occur due to the underlying discreteness of the systems and random fluctuations in molecular numbers. Numerous stochastic, approximate stochastic and hybrid simulation methods have been proposed in the literature. In this article, they are systematically reviewed in order to guide the researcher and help her find the appropriate method for a specific problem.
    PMID: 19151097 [PubMed - as supplied by publisher] (Source: B...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2117181</comments>
            <pubDate>Fri, 16 Jan 2009 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">2117181</guid>        </item>
        <item>
            <title>Domain mobility in proteins: functional and evolutionary implications.</title>
            <link>http://www.medworm.com/index.php?rid=2117180&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19151098%26dopt%3DAbstract</link>
            <description>Authors: Basu MK, Poliakov E, Rogozin IB
    A substantial fraction of eukaryotic proteins contains multiple domains, some of which show a tendency to occur in diverse domain architectures and can be considered mobile (or 'promiscuous'). These promiscuous domains are typically involved in protein-protein interactions and play crucial roles in interaction networks, particularly those contributing to signal transduction. They also play a major role in creating diversity of protein domain architecture in the proteome. It is now apparent that promiscuity is a volatile and relatively fast-changing feature in evolution, and that only a few domains retain their promiscuity status throughout evolution. Many such domains attained their promiscuity status independently in different lineages. Only re...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2117180</comments>
            <pubDate>Fri, 16 Jan 2009 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">2117180</guid>        </item>
        <item>
            <title>Moby and Moby 2: Creatures of the Deep (Web).</title>
            <link>http://www.medworm.com/index.php?rid=2117179&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19151099%26dopt%3DAbstract</link>
            <description>Authors: Vandervalk BP, McCarthy EL, Wilkinson MD
    Facile and meaningful integration of data from disparate resources is the 'holy grail' of bioinformatics. Some resources have begun to address this problem by providing their data using Semantic Web standards, specifically the Resource Description Framework (RDF) and the Web Ontology Language (OWL). Unfortunately, adoption of Semantic Web standards has been slow overall, and even in cases where the standards are being utilized, interconnectivity between resources is rare. In response, we have seen the emergence of centralized 'semantic warehouses' that collect public data from third parties, integrate it, translate it into OWL/RDF and provide it to the community as a unified and queryable resource. One limitation of the warehouse approa...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2117179</comments>
            <pubDate>Fri, 16 Jan 2009 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">2117179</guid>        </item>
        <item>
            <title>Simulation of DNA sequence evolution under models of recent directional selection.</title>
            <link>http://www.medworm.com/index.php?rid=2066111&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19109303%26dopt%3DAbstract</link>
            <description>Authors: Kim Y, Wiehe T
    Computer simulation is an essential tool in the analysis of DNA sequence variation for mapping events of recent adaptive evolution in the genome. Various simulation methods are employed to predict the signature of selection in sequence variation. The most informative and efficient method currently in use is coalescent simulation. However, this method is limited to simple models of directional selection. Whole-population forward-in-time simulations are the alternative to coalescent simulations for more complex models. The notorious problem of excessive computational cost in forward-in-time simulations can be overcome by various simplifying amendments. Overall, the success of simulations depends on the creative application of some population genetic theory to the ...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2066111</comments>
            <pubDate>Wed, 24 Dec 2008 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">2066111</guid>        </item>
        <item>
            <title>Towards the integrated analysis, visualization and reconstruction of microbial gene regulatory networks.</title>
            <link>http://www.medworm.com/index.php?rid=2042288&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19074493%26dopt%3DAbstract</link>
            <description>Authors: Baumbach J, Tauch A, Rahmann S
    To handle changing environmental surroundings and to manage unfavorable conditions, microbial organisms have evolved complex transcriptional regulatory networks. To comprehensively analyze these gene regulatory networks, several online available databases and analysis platforms have been implemented and established. In this article, we address the typical cycle of scientific knowledge exploration and integration in the area of procaryotic transcriptional gene regulation. We briefly review five popular, publicly available systems that support (i) the integration of existing knowledge, (ii) visualization capabilities and (iii) computer analysis to predict promising wet lab targets. We exemplify the benefits of such integrated data analysis platform...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2042288</comments>
            <pubDate>Fri, 12 Dec 2008 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">2042288</guid>        </item>
        <item>
            <title>Building a knowledge base for systems pathology.</title>
            <link>http://www.medworm.com/index.php?rid=2042289&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19073714%26dopt%3DAbstract</link>
            <description>Authors: Michael H, Hogan J, Kel A, Kel-Margoulis O, Schacherer F, Voss N, Wingender E
    Translating the exponentially growing amount of omics data into knowledge usable for a personalized medicine approach poses a formidable challenge. In this article-taking diabetes as a use case-we present strategies for developing data repositories into computer-accessible knowledge sources that can be used for a systemic view on the molecular causes of diseases, thus laying the foundation for systems pathology.
    PMID: 19073714 [PubMed - as supplied by publisher] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2042289</comments>
            <pubDate>Wed, 10 Dec 2008 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">2042289</guid>        </item>
        <item>
            <title>Building biomedical web communities using a semantically aware content management system.</title>
            <link>http://www.medworm.com/index.php?rid=2022533&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19060302%26dopt%3DAbstract</link>
            <description>Authors: Das S, Girard L, Green T, Weitzman L, Lewis-Bowen A, Clark T
    Web-based biomedical communities are becoming an increasingly popular vehicle for sharing information amongst researchers and are fast gaining an online presence. However, information organization and exchange in such communities is usually unstructured, rendering interoperability between communities difficult. Furthermore, specialized software to create such communities at low cost-targeted at the specific common information requirements of biomedical researchers-has been largely lacking. At the same time, a growing number of biological knowledge bases and biomedical resources are being structured for the Semantic Web. Several groups are creating reference ontologies for the biomedical domain, actively publishing co...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2022533</comments>
            <pubDate>Sat, 06 Dec 2008 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">2022533</guid>        </item>
        <item>
            <title>Facts from text: can text mining help to scale-up high-quality manual curation of gene products with ontologies?</title>
            <link>http://www.medworm.com/index.php?rid=2022532&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19060303%26dopt%3DAbstract</link>
            <description>Authors: Winnenburg R, W&amp;#xE4;chter T, Plake C, Doms A, Schroeder M
    The biomedical literature can be seen as a large integrated, but unstructured data repository. Extracting facts from literature and making them accessible is approached from two directions: manual curation efforts develop ontologies and vocabularies to annotate gene products based on statements in papers. Text mining aims to automatically identify entities and their relationships in text using information retrieval and natural language processing techniques. Manual curation is highly accurate but time consuming, and does not scale with the ever increasing growth of literature. Text mining as a high-throughput computational technique scales well, but is error-prone due to the complexity of natural language. How can both...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2022532</comments>
            <pubDate>Sat, 06 Dec 2008 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">2022532</guid>        </item>
        <item>
            <title>Data curation + process curation=data integration + science.</title>
            <link>http://www.medworm.com/index.php?rid=2022531&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19060304%26dopt%3DAbstract</link>
            <description>This article will brief the community on the current state of the art and the current challenges for process curation, both within and without the Life Sciences.
    PMID: 19060304 [PubMed - as supplied by publisher] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2022531</comments>
            <pubDate>Sat, 06 Dec 2008 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">2022531</guid>        </item>
        <item>
            <title>A pitfall of wiki solution for biological databases.</title>
            <link>http://www.medworm.com/index.php?rid=2022530&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19060305%26dopt%3DAbstract</link>
            <description>Authors: Arita M
    Not a few biologists tend to consider wiki as a solution to manage and reorganize data by a community. However, in its basic functionality, wiki lacks a measure to check data consistency and is not suitable for a database. To circumvent this pitfall, installation of page dependency through in-line page searches is necessary. We also introduce two existing approaches that support in-line queries.
    PMID: 19060305 [PubMed - as supplied by publisher] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2022530</comments>
            <pubDate>Sat, 06 Dec 2008 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">2022530</guid>        </item>
        <item>
            <title>Linked data and provenance in biological data webs.</title>
            <link>http://www.medworm.com/index.php?rid=2022529&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19060306%26dopt%3DAbstract</link>
            <description>This article presents design patterns for representing and querying provenance information relating to mapping links between heterogeneous data from sources in the domain of functional genomics. We illustrate the use of named resource description framework (RDF) graphs at different levels of granularity to make provenance assertions about linked data, and demonstrate that these assertions are sufficient to support requirements including data currency, integrity, evidential support and historical queries.
    PMID: 19060306 [PubMed - as supplied by publisher] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=2022529</comments>
            <pubDate>Sat, 06 Dec 2008 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">2022529</guid>        </item>
        <item>
            <title>Data and knowledge integration in the life sciences.</title>
            <link>http://www.medworm.com/index.php?rid=1935016&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18980960%26dopt%3DAbstract</link>
            <description>Authors: Philippi S
    
    PMID: 18980960 [PubMed - as supplied by publisher] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1935016</comments>
            <pubDate>Sun, 02 Nov 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1935016</guid>        </item>
        <item>
            <title>Models of coding sequence evolution.</title>
            <link>http://www.medworm.com/index.php?rid=1921956&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18971241%26dopt%3DAbstract</link>
            <description>Authors: Delport W, Scheffler K, Seoighe C
    Probabilistic models of sequence evolution are in widespread use in phylogenetics and molecular sequence evolution. These models have become increasingly sophisticated and combined with statistical model comparison techniques have helped to shed light on how genes and proteins evolve. Models of codon evolution have been particularly useful, because, in addition to providing a significant improvement in model realism for protein-coding sequences, codon models can also be designed to test hypotheses about the selective pressures that shape the evolution of the sequences. Such models typically assume a phylogeny and can be used to identify sites or lineages that have evolved adaptively. Recently some of the key assumptions that underlie phylogene...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1921956</comments>
            <pubDate>Wed, 29 Oct 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1921956</guid>        </item>
        <item>
            <title>Knowledge-based expert systems and a proof-of-concept case study for multiple sequence alignment construction and analysis.</title>
            <link>http://www.medworm.com/index.php?rid=1921955&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18971242%26dopt%3DAbstract</link>
            <description>Authors: Aniba MR, Siguenza S, Friedrich A, Plewniak F, Poch O, Marchler-Bauer A, Thompson JD
    The traditional approach to bioinformatics analyses relies on independent task-specific services and applications, using different input and output formats, often idiosyncratic, and frequently not designed to inter-operate. In general, such analyses were performed by experts who manually verified the results obtained at each step in the process. Today, the amount of bioinformatics information continuously being produced means that handling the various applications used to study this information presents a major data management and analysis challenge to researchers. It is now impossible to manually analyse all this information and new approaches are needed that are capable of processing the lar...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1921955</comments>
            <pubDate>Wed, 29 Oct 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1921955</guid>        </item>
        <item>
            <title>Bringing Web 2.0 to bioinformatics.</title>
            <link>http://www.medworm.com/index.php?rid=1866271&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18842678%26dopt%3DAbstract</link>
            <description>In this report, we discuss the potential of Web 2.0 technologies to transcend this model and enhance bioinformatics research. We propose a Web 2.0-based Scientific Social Community (SSC) model for the implementation of these technologies. By establishing a social, collective and collaborative platform for data creation, sharing and integration, we promote a web services-based pipeline featuring web services for computer-to-computer data exchange as users add value. This pipeline aims to simplify data integration and creation, to realize automatic analysis, and to facilitate reuse and sharing of data. SSC can foster collaboration and harness collective intelligence to create and discover new knowledge. In addition to its research potential, we also describe its potential role as an e-learni...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1866271</comments>
            <pubDate>Wed, 08 Oct 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1866271</guid>        </item>
        <item>
            <title>Gene-set analysis and reduction.</title>
            <link>http://www.medworm.com/index.php?rid=1857208&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18836208%26dopt%3DAbstract</link>
            <description>Authors: Dinu I, Potter JD, Mueller T, Liu Q, Adewale AJ, Jhangri GS, Einecke G, Famulski KS, Halloran P, Yasui Y
    Gene-set analysis aims to identify differentially expressed gene sets (pathways) by a phenotype in DNA microarray studies. We review here important methodological aspects of gene-set analysis and illustrate them with varying performance of several methods proposed in the literature. We emphasize the importance of distinguishing between 'self-contained' versus 'competitive' methods, following Goeman and B&amp;#xFC;hlmann. We also discuss reducing a gene set to its subset, consisting of 'core members' that chiefly contribute to the statistical significance of the differential expression of the initial gene set by phenotype. Significance analysis of microarray for gene-set reducti...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1857208</comments>
            <pubDate>Sat, 04 Oct 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1857208</guid>        </item>
        <item>
            <title>Literature mining in support of drug discovery.</title>
            <link>http://www.medworm.com/index.php?rid=1838459&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18820304%26dopt%3DAbstract</link>
            <description>Authors: Agarwal P, Searls DB
    The drug discovery enterprise provides strong drivers for data integration. While attention in this arena has tended to focus on integration of primary data from omics and other large platform technologies contributing to drug discovery and development, the scientific literature remains a major source of information valuable to pharmaceutical enterprises, and therefore tools for mining such data and integrating it with other sources are of vital interest and economic impact. This review provides a brief overview of approaches to literature mining as they relate to drug discovery, and offers an illustrative case study of a 'lightweight' approach we have implemented within an industrial context.
    PMID: 18820304 [PubMed - as supplied by publisher] (Source:...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1838459</comments>
            <pubDate>Sat, 27 Sep 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1838459</guid>        </item>
        <item>
            <title>Web-based applications for building, managing and analysing kinetic models of biological systems.</title>
            <link>http://www.medworm.com/index.php?rid=1816594&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18805901%26dopt%3DAbstract</link>
            <description>In this report, we evaluate the capabilities and characteristics of current web-based tools in systems biology and identify desirable features, limitations and bottlenecks for further improvements in terms of usability and functionality. A short discussion on software architecture issues involved in web-based applications and the approaches taken by existing tools is included for those interested in developing their own simulation applications.
    PMID: 18805901 [PubMed - as supplied by publisher] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1816594</comments>
            <pubDate>Fri, 19 Sep 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1816594</guid>        </item>
        <item>
            <title>Categorization of services for seeking information in biomedical literature: a typology for improvement of practice.</title>
            <link>http://www.medworm.com/index.php?rid=1661907&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18660511%26dopt%3DAbstract</link>
            <description>Authors: Kim JJ, Rebholz-Schuhmann D
    Biomedical researchers have to efficiently explore the scientific literature, keeping the focus on their research. This goal can only be achieved if the available means for accessing the literature meet the researchers' retrieval needs and if they understand how the tools filter the perpetually increasing number of documents. We have examined existing web-based services for information retrieval in order to give users guidance to improve their everyday practice of literature analysis. We propose two dimensions along which the services may be categorized: categories of input and output formats; and categories of behavioural usage. The categorization would be helpful for biologists to understand the differences in the input and output formats and the ...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1661907</comments>
            <pubDate>Sat, 26 Jul 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1661907</guid>        </item>
        <item>
            <title>Identification of replication origins in prokaryotic genomes.</title>
            <link>http://www.medworm.com/index.php?rid=1661906&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18660512%26dopt%3DAbstract</link>
            <description>Authors: Sernova NV, Gelfand MS
    The availability of hundreds of complete bacterial genomes has created new challenges and simultaneously opportunities for bioinformatics. In the area of statistical analysis of genomic sequences, the studies of nucleotide compositional bias and gene bias between strands and replichores paved way to the development of tools for prediction of bacterial replication origins. Only a few (about 20) origin regions for eubacteria and archaea have been proven experimentally. One reason for that may be that this is now considered as an essentially bioinformatics problem, where predictions are sufficiently reliable not to run labor-intensive experiments, unless specifically needed. Here we describe the main existing approaches to the identification of replication ...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1661906</comments>
            <pubDate>Sat, 26 Jul 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1661906</guid>        </item>
        <item>
            <title>Experience using web services for biological sequence analysis.</title>
            <link>http://www.medworm.com/index.php?rid=1628015&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18621748%26dopt%3DAbstract</link>
            <description>Authors: Stockinger H, Attwood T, Chohan SN, C&amp;#xF4;t&amp;#xE9; R, Cudr&amp;#xE9;-Mauroux P, Falquet L, Fernandes P, Finn RD, Hupponen T, Korpelainen E, Labarga A, Laugraud A, Lima T, Pafilis E, Pagni M, Pettifer S, Phan I, Rahman N
    Programmatic access to data and tools through the web using so-called web services has an important role to play in bioinformatics. In this article, we discuss the most popular approaches based on SOAP/WS-I and REST and describe our, a cross section of the community, experiences with providing and using web services in the context of biological sequence analysis. We briefly review main technological approaches as well as best practice hints that are useful for both users and developers. Finally, syntactic and semantic data integration issues with multiple web servi...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1628015</comments>
            <pubDate>Fri, 11 Jul 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1628015</guid>        </item>
        <item>
            <title>Detecting short tandem repeats from genome data: opening the software black box.</title>
            <link>http://www.medworm.com/index.php?rid=1628016&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18621747%26dopt%3DAbstract</link>
            <description>This article introduces the major concepts behind repeat detecting software essential for informed tool selection. We reflect on issues such as parameter settings and program bias, as well as redundancy filtering and efficiency using examples from the currently available range of programs, to provide an integrated comparison and practical guide to microsatellite detecting programs.
    PMID: 18621747 [PubMed - as supplied by publisher] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1628016</comments>
            <pubDate>Thu, 10 Jul 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1628016</guid>        </item>
        <item>
            <title>Recent developments in the MAFFT multiple sequence alignment program.</title>
            <link>http://www.medworm.com/index.php?rid=1598727&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18372315%26dopt%3DAbstract</link>
            <description>Authors: Katoh K, Toh H
    The accuracy and scalability of multiple sequence alignment (MSA) of DNAs and proteins have long been and are still important issues in bioinformatics. To rapidly construct a reasonable MSA, we developed the initial version of the MAFFT program in 2002. MSA software is now facing greater challenges in both scalability and accuracy than those of 5 years ago. As increasing amounts of sequence data are being generated by large-scale sequencing projects, scalability is now critical in many situations. The requirement of accuracy has also entered a new stage since the discovery of functional noncoding RNAs (ncRNAs); the secondary structure should be considered for constructing a high-quality alignment of distantly related ncRNAs. To deal with these problems, in 2007,...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598727</comments>
            <pubDate>Tue, 01 Jul 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598727</guid>        </item>
        <item>
            <title>MEGA: a biologist-centric software for evolutionary analysis of DNA and protein sequences.</title>
            <link>http://www.medworm.com/index.php?rid=1598726&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18417537%26dopt%3DAbstract</link>
            <description>Authors: Kumar S, Nei M, Dudley J, Tamura K
    The Molecular Evolutionary Genetics Analysis (MEGA) software is a desktop application designed for comparative analysis of homologous gene sequences either from multigene families or from different species with a special emphasis on inferring evolutionary relationships and patterns of DNA and protein evolution. In addition to the tools for statistical analysis of data, MEGA provides many convenient facilities for the assembly of sequence data sets from files or web-based repositories, and it includes tools for visual presentation of the results obtained in the form of interactive phylogenetic trees and evolutionary distance matrices. Here we discuss the motivation, design principles and priorities that have shaped the development of MEGA. We ...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598726</comments>
            <pubDate>Tue, 01 Jul 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598726</guid>        </item>
        <item>
            <title>IMGT, a system and an ontology that bridge biological and computational spheres in bioinformatics.</title>
            <link>http://www.medworm.com/index.php?rid=1598724&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18424816%26dopt%3DAbstract</link>
            <description>Authors: Lefranc MP, Giudicelli V, Regnier L, Duroux P
    IMGT, the international ImMunoGeneTics information system (http://imgt.cines.fr), is the reference in immunogenetics and immunoinformatics. IMGT standardizes and manages the complex immunogenetic data that include the immunoglobulins (IG) or antibodies, the T cell receptors (TR), the major histocompatibility complex (MHC) and the related proteins of the immune system (RPI), which belong to the immunoglobulin superfamily (IgSF) and the MHC superfamily (MhcSF). The accuracy and consistency of IMGT data and the coherence between the different IMGT components (databases, tools and Web resources) are based on IMGT-ONTOLOGY, the first ontology for immunogenetics and immunoinformatics. IMGT-ONTOLOGY manages the immunogenetics knowledge th...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598724</comments>
            <pubDate>Tue, 01 Jul 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598724</guid>        </item>
        <item>
            <title>Protein structure databases with new web services for structural biology and biomedical research.</title>
            <link>http://www.medworm.com/index.php?rid=1598723&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18430752%26dopt%3DAbstract</link>
            <description>Authors: Standley DM, Kinjo AR, Kinoshita K, Nakamura H
    The Protein Data Bank Japan (PDBj) curates, edits and distributes protein structural data as a member of the worldwide Protein Data Bank (wwPDB) and currently processes approximately 25-30% of all deposited data in the world. Structural information is enhanced by the addition of biological and biochemical functional data as well as experimental details extracted from the literature and other databases. Several applications have been developed at PDBj for structural biology and biomedical studies: (i) a Java-based molecular graphics viewer, jV; (ii) display of electron density maps for the evaluation of structure quality; (iii) an extensive database of molecular surfaces for functional sites, eF-site, as well as a search service fo...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598723</comments>
            <pubDate>Tue, 01 Jul 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598723</guid>        </item>
        <item>
            <title>The TRANSFAC project as an example of framework technology that supports the analysis of genomic regulation.</title>
            <link>http://www.medworm.com/index.php?rid=1598721&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18436575%26dopt%3DAbstract</link>
            <description>Authors: Wingender E
    Since its beginning as a data collection more than 20 years ago, the TRANSFAC project underwent an evolution to become the basis for a complex platform for the description and analysis of gene regulatory events and networks. In the following, I describe what the original concepts were, what their present status is and how they may be expected to contribute to future system biology approaches.
    PMID: 18436575 [PubMed - indexed for MEDLINE] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598721</comments>
            <pubDate>Tue, 01 Jul 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598721</guid>        </item>
        <item>
            <title>Computational intelligence approaches for pattern discovery in biological systems.</title>
            <link>http://www.medworm.com/index.php?rid=1598719&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18460474%26dopt%3DAbstract</link>
            <description>Authors: Fogel GB
    Biology, chemistry and medicine are faced by tremendous challenges caused by an overwhelming amount of data and the need for rapid interpretation. Computational intelligence (CI) approaches such as artificial neural networks, fuzzy systems and evolutionary computation are being used with increasing frequency to contend with this problem, in light of noise, non-linearity and temporal dynamics in the data. Such methods can be used to develop robust models of processes either on their own or in combination with standard statistical approaches. This is especially true for database mining, where modeling is a key component of scientific understanding. This review provides an introduction to current CI methods, their application to biological problems, and concludes with a ...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598719</comments>
            <pubDate>Tue, 01 Jul 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598719</guid>        </item>
        <item>
            <title>VisANT: an integrative framework for networks in systems biology.</title>
            <link>http://www.medworm.com/index.php?rid=1598717&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18463131%26dopt%3DAbstract</link>
            <description>Authors: Hu Z, Snitkin ES, DeLisi C
    The essence of a living cell is adaptation to a changing environment, and a central goal of modern cell biology is to understand adaptive change under normal and pathological conditions. Because the number of components is large, and processes and conditions are many, visual tools are useful in providing an overview of relations that would otherwise be far more difficult to assimilate. Historically, representations were static pictures, with genes and proteins represented as nodes, and known or inferred correlations between them (links) represented by various kinds of lines. The modern challenge is to capture functional hierarchies and adaptation to environmental change, and to discover pathways and processes embedded in known data, but not currently...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598717</comments>
            <pubDate>Tue, 01 Jul 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598717</guid>        </item>
        <item>
            <title>Bioinformatics, multiscale modeling and the IUPS Physiome Project.</title>
            <link>http://www.medworm.com/index.php?rid=1598716&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18477639%26dopt%3DAbstract</link>
            <description>Authors: Hunter PJ, Crampin EJ, Nielsen PM
    Multiscale modeling is required for linking physiological processes operating at the organ and tissue levels to signal transduction networks and other subcellular processes. Several XML markup languages, including CellML, have been developed to encode models and to facilitate the building of model repositories and general purpose software tools. Progress in this area is described and illustrated with reference to the heart Physiome Project which aims to understand cardiac arrhythmias in terms of structure-function relations from proteins up to cells, tissues and organs.
    PMID: 18477639 [PubMed - indexed for MEDLINE] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598716</comments>
            <pubDate>Tue, 01 Jul 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598716</guid>        </item>
        <item>
            <title>Critical technologies for bioinformatics.</title>
            <link>http://www.medworm.com/index.php?rid=1598715&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18499720%26dopt%3DAbstract</link>
            <description>Authors: Brusic V, Ranganathan S
    
    PMID: 18499720 [PubMed - indexed for MEDLINE] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598715</comments>
            <pubDate>Tue, 01 Jul 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598715</guid>        </item>
        <item>
            <title>A structured approach for the engineering of biochemical network models, illustrated for signalling pathways.</title>
            <link>http://www.medworm.com/index.php?rid=1598713&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18573813%26dopt%3DAbstract</link>
            <description>Authors: Breitling R, Gilbert D, Heiner M, Orton R
    Quantitative models of biochemical networks (signal transduction cascades, metabolic pathways, gene regulatory circuits) are a central component of modern systems biology. Building and managing these complex models is a major challenge that can benefit from the application of formal methods adopted from theoretical computing science. Here we provide a general introduction to the field of formal modelling, which emphasizes the intuitive biochemical basis of the modelling process, but is also accessible for an audience with a background in computing science and/or model engineering. We show how signal transduction cascades can be modelled in a modular fashion, using both a qualitative approach-qualitative Petri nets, and quantitative app...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598713</comments>
            <pubDate>Mon, 23 Jun 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598713</guid>        </item>
        <item>
            <title>Penalized feature selection and classification in bioinformatics.</title>
            <link>http://www.medworm.com/index.php?rid=1598714&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18562478%26dopt%3DAbstract</link>
            <description>Authors: Ma S, Huang J
    In bioinformatics studies, supervised classification with high-dimensional input variables is frequently encountered. Examples routinely arise in genomic, epigenetic and proteomic studies. Feature selection can be employed along with classifier construction to avoid over-fitting, to generate more reliable classifier and to provide more insights into the underlying causal relationships. In this article, we provide a review of several recently developed penalized feature selection and classification techniques-which belong to the family of embedded feature selection methods-for bioinformatics studies with high-dimensional input. Classification objective functions, penalty functions and computational algorithms are discussed. Our goal is to make interested researche...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598714</comments>
            <pubDate>Wed, 18 Jun 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598714</guid>        </item>
        <item>
            <title>The Beta Workbench: a computational tool to study the dynamics of biological systems.</title>
            <link>http://www.medworm.com/index.php?rid=1598718&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18463130%26dopt%3DAbstract</link>
            <description>Authors: Dematt&amp;#xE9; L, Priami C, Romanel A
    We introduce the Beta Workbench (BWB), a scalable tool built on top of the newly defined BlenX language to model, simulate and analyse biological systems. We show the features and the incremental modelling process supported by the BWB on a running example based on the mitogen-activated kinase pathway. Finally, we provide a comparison with related approaches and some hints for future extensions.
    PMID: 18463130 [PubMed - as supplied by publisher] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598718</comments>
            <pubDate>Wed, 07 May 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598718</guid>        </item>
        <item>
            <title>ROC analysis: applications to the classification of biological sequences and 3D structures.</title>
            <link>http://www.medworm.com/index.php?rid=1598740&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18192302%26dopt%3DAbstract</link>
            <description>Authors: Sonego P, Kocsor A, Pongor S
    ROC ('receiver operator characteristics') analysis is a visual as well as numerical method used for assessing the performance of classification algorithms, such as those used for predicting structures and functions from sequence data. This review summarizes the fundamental concepts of ROC analysis and the interpretation of results using examples of sequence and structure comparison. We overview the available programs and provide evaluation guidelines for genomic/proteomic data, with particular regard to applications to large and heterogeneous databases used in bioinformatics.
    PMID: 18192302 [PubMed - indexed for MEDLINE] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598740</comments>
            <pubDate>Thu, 01 May 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598740</guid>        </item>
        <item>
            <title>Two interactive Bioinformatics courses at the Bielefeld University Bioinformatics Server.</title>
            <link>http://www.medworm.com/index.php?rid=1598739&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18199576%26dopt%3DAbstract</link>
            <description>Authors: Sczyrba A, Konermann S, Giegerich R
    Conferences in computational biology continue to provide tutorials on classical and new methods in the field. This can be taken as an indicator that education is still a bottleneck in our field's process of becoming an established scientific discipline. Bielefeld University has been one of the early providers of bioinformatics education, both locally and via the internet. The Bielefeld Bioinformatics Server (BiBiServ) offers a variety of older and new materials. Here, we report on two online courses made available recently, one introductory and one on the advanced level: (i) SADR: Sequence Analysis with Distributed Resources (http://bibiserv.techfak.uni-bielefeld.de/sadr/) and (ii) ADP: Algebraic Dynamic Programming in Bioinformatics (http:/...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598739</comments>
            <pubDate>Thu, 01 May 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598739</guid>        </item>
        <item>
            <title>Gene-set approach for expression pattern analysis.</title>
            <link>http://www.medworm.com/index.php?rid=1598738&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18202032%26dopt%3DAbstract</link>
            <description>Authors: Nam D, Kim SY
    Recently developed gene set analysis methods evaluate differential expression patterns of gene groups instead of those of individual genes. This approach especially targets gene groups whose constituents show subtle but coordinated expression changes, which might not be detected by the usual individual gene analysis. The approach has been quite successful in deriving new information from expression data, and a number of methods and tools have been developed intensively in recent years. We review those methods and currently available tools, classify them according to the statistical methods employed, and discuss their pros and cons. We also discuss several interesting extensions to the methods.
    PMID: 18202032 [PubMed - indexed for MEDLINE] (Source: Briefings i...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598738</comments>
            <pubDate>Thu, 01 May 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598738</guid>        </item>
        <item>
            <title>The BREW workshop series: a stimulating experience in PhD education.</title>
            <link>http://www.medworm.com/index.php?rid=1598737&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18216087%26dopt%3DAbstract</link>
            <description>We describe the BREW experience and argue that this type of event constitutes an attractive component of PhD education in computational biology and beyond.
    PMID: 18216087 [PubMed - indexed for MEDLINE] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598737</comments>
            <pubDate>Thu, 01 May 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598737</guid>        </item>
        <item>
            <title>Interoperability with Moby 1.0--it's better than sharing your toothbrush!</title>
            <link>http://www.medworm.com/index.php?rid=1598736&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18238804%26dopt%3DAbstract</link>
            <description>Authors:  , Wilkinson MD, Senger M, Kawas E, Bruskiewich R, Gouzy J, Noirot C, Bardou P, Ng A, Haase D, Saiz Ede A, Wang D, Gibbons F, Gordon PM, Sensen CW, Carrasco JM, Fern&amp;#xE1;ndez JM, Shen L, Links M, Ng M, Opushneva N, Neerincx PB, Leunissen JA, Ernst R, Twigger S, Usadel B, Good B, Wong Y, Stein L, Crosby W, Karlsson J, Royo R, P&amp;#xE1;rraga I, Ram&amp;#xED;rez S, Gelpi JL, Trelles O, Pisano DG, Jimenez N, Kerhornou A, Rosset R, Zamacola L, Tarraga J, Huerta-Cepas J, Carazo JM, Dopazo J, Guigo R, Navarro A, Orozco M, Valencia A, Claros MG, P&amp;#xE9;rez AJ, Aldana J, Rojano MM, Fernandez-Santa Cruz R, Navas I, Schiltz G, Farmer A, Gessler D, Schoof H, Groscurth A
    The BioMoby project was initiated in 2001 from within the model organism database community. It aimed to standardize methodol...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598736</comments>
            <pubDate>Thu, 01 May 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598736</guid>        </item>
        <item>
            <title>A review of bioinformatics education in Germany.</title>
            <link>http://www.medworm.com/index.php?rid=1598731&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18310676%26dopt%3DAbstract</link>
            <description>We describe the establishment of bioinformatics in Germany and give an overview of current bioinformatics education in this country, from the perspective of the practitioner. The aim of this study is to demonstrate development of a strong bioinformatics education at German universities and research institutes during the last years. Beginning with a definition of the multi-disciplinary field bioinformatics, we give a survey of government initiatives in Germany in support of this field, which resulted in a wide spectrum of courses. To the best of our knowledge, we compile all ongoing courses at universities and research institutes. Five case studies featuring university courses with different educational focus illustrate the variety of efforts. In this context we also discuss the main compon...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598731</comments>
            <pubDate>Thu, 01 May 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598731</guid>        </item>
        <item>
            <title>Pfam 10 years on: 10,000 families and still growing.</title>
            <link>http://www.medworm.com/index.php?rid=1598729&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18344544%26dopt%3DAbstract</link>
            <description>Authors: Sammut SJ, Finn RD, Bateman A
    Classifications of proteins into groups of related sequences are in some respects like a periodic table for biology, allowing us to understand the underlying molecular biology of any organism. Pfam is a large collection of protein domains and families. Its scientific goal is to provide a complete and accurate classification of protein families and domains. The next release of the database will contain over 10,000 entries, which leads us to reflect on how far we are from completing this work. Currently Pfam matches 72% of known protein sequences, but for proteins with known structure Pfam matches 95%, which we believe represents the likely upper bound. Based on our analysis a further 28,000 families would be required to achieve this level of covera...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598729</comments>
            <pubDate>Thu, 01 May 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598729</guid>        </item>
        <item>
            <title>Biodiversity informatics: the challenge of linking data and the role of shared identifiers.</title>
            <link>http://www.medworm.com/index.php?rid=1598720&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18445641%26dopt%3DAbstract</link>
            <description>Authors: Page RD
    A major challenge facing biodiversity informatics is integrating data stored in widely distributed databases. Initial efforts have relied on taxonomic names as the shared identifier linking records in different databases. However, taxonomic names have limitations as identifiers, being neither stable nor globally unique, and the pace of molecular taxonomic and phylogenetic research means that a lot of information in public sequence databases is not linked to formal taxonomic names. This review explores the use of other identifiers, such as specimen codes and GenBank accession numbers, to link otherwise disconnected facts in different databases. The structure of these links can also be exploited using the PageRank algorithm to rank the results of searches on biodiversity...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598720</comments>
            <pubDate>Tue, 29 Apr 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598720</guid>        </item>
        <item>
            <title>A critical examination of stoichiometric and path-finding approaches to metabolic pathways.</title>
            <link>http://www.medworm.com/index.php?rid=1598722&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18436574%26dopt%3DAbstract</link>
            <description>Authors: Planes FJ, Beasley JE
    Advances in the field of genomics have enabled computational analysis of metabolic pathways at the genome scale. Singular attention has been devoted in the literature to stoichiometric approaches, and path-finding approaches, to metabolic pathways. Stoichiometric approaches make use of reaction stoichiometry when trying to determine metabolic pathways. Stoichiometric approaches involve elementary flux modes and extreme pathways. In contrast, path-finding approaches propose an alternative view based on graph theory in which reaction stoichiometry is not considered. Path-finding approaches use shortest path and k-shortest path concepts. In this article we give a critical overview of the theory, applications and key research challenges of stoichiometric and ...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598722</comments>
            <pubDate>Thu, 24 Apr 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598722</guid>        </item>
        <item>
            <title>The relative value of operon predictions.</title>
            <link>http://www.medworm.com/index.php?rid=1598725&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18420711%26dopt%3DAbstract</link>
            <description>Authors: Brouwer RW, Kuipers OP, Hijum SA
    For most organisms, computational operon predictions are the only source of genome-wide operon information. Operon prediction methods described in literature are based on (a combination of) the following five criteria: (i) intergenic distance, (ii) conserved gene clusters, (iii) functional relation, (iv) sequence elements and (v) experimental evidence. The performance estimates of operon predictions reported in literature cannot directly be compared due to differences in methods and data used in these studies. Here, we survey the current status of operon prediction methods. Based on a comparison of the performance of operon predictions on Escherichia coli and Bacillus subtilis we conclude that there is still room for improvement. We expect that...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598725</comments>
            <pubDate>Thu, 17 Apr 2008 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598725</guid>        </item>
        <item>
            <title>Computational methods for the comparative quantification of proteins in label-free LCn-MS experiments.</title>
            <link>http://www.medworm.com/index.php?rid=1598755&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17905794%26dopt%3DAbstract</link>
            <description>Authors: Wong JW, Sullivan MJ, Cagney G
    Liquid chromatography (LC) coupled to electrospray mass spectrometry (MS) is well established in high-throughput proteomics. The technology enables rapid identification of large numbers of proteins in a relatively short time. Comparative quantification of identified proteins from different samples is often regarded as the next step in proteomics experiments enabling the comparison of protein expression in different proteomes. Differential labeling of samples using stable isotope incorporation or conjugation is commonly used to compare protein levels between samples but these procedures are difficult to carry out in the laboratory and for large numbers of samples. Recently, comparative quantification of label-free LC(n)-MS proteomics data has emer...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598755</comments>
            <pubDate>Sat, 01 Mar 2008 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598755</guid>        </item>
        <item>
            <title>The HUPO proteomics standards initiative--easing communication and minimizing data loss in a changing world.</title>
            <link>http://www.medworm.com/index.php?rid=1598743&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18065433%26dopt%3DAbstract</link>
            <description>This article will provide an update on the work of this group, the creation and implementation of these standards and the standards-compliant data repositories being established as result of their efforts.
    PMID: 18065433 [PubMed - indexed for MEDLINE] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598743</comments>
            <pubDate>Sat, 01 Mar 2008 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598743</guid>        </item>
        <item>
            <title>Information quality in proteomics.</title>
            <link>http://www.medworm.com/index.php?rid=1598735&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18281347%26dopt%3DAbstract</link>
            <description>Authors: Stead DA, Paton NW, Missier P, Embury SM, Hedeler C, Jin B, Brown AJ, Preece A
    Proteomics, the study of the protein complement of a biological system, is generating increasing quantities of data from rapidly developing technologies employed in a variety of different experimental workflows. Experimental processes, e.g. for comparative 2D gel studies or LC-MS/MS analyses of complex protein mixtures, involve a number of steps: from experimental design, through wet and dry lab operations, to publication of data in repositories and finally to data annotation and maintenance. The presence of inaccuracies throughout the processing pipeline, however, results in data that can be untrustworthy, thus offsetting the benefits of high-throughput technology. While researchers and practitione...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598735</comments>
            <pubDate>Sat, 01 Mar 2008 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598735</guid>        </item>
        <item>
            <title>Computational proteomics: management and analysis of proteomics data.</title>
            <link>http://www.medworm.com/index.php?rid=1598734&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18310104%26dopt%3DAbstract</link>
            <description>Authors: Cannataro M
    
    PMID: 18310104 [PubMed - indexed for MEDLINE] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598734</comments>
            <pubDate>Sat, 01 Mar 2008 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598734</guid>        </item>
        <item>
            <title>Machine learning methods for predictive proteomics.</title>
            <link>http://www.medworm.com/index.php?rid=1598733&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18310105%26dopt%3DAbstract</link>
            <description>Authors: Barla A, Jurman G, Riccadonna S, Merler S, Chierici M, Furlanello C
    The search for predictive biomarkers of disease from high-throughput mass spectrometry (MS) data requires a complex analysis path. Preprocessing and machine-learning modules are pipelined, starting from raw spectra, to set up a predictive classifier based on a shortlist of candidate features. As a machine-learning problem, proteomic profiling on MS data needs caution like the microarray case. The risk of overfitting and of selection bias effects is pervasive: not only potential features easily outnumber samples by 10(3) times, but it is easy to neglect information-leakage effects during preprocessing from spectra to peaks. The aim of this review is to explain how to build a general purpose design analysis prot...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598733</comments>
            <pubDate>Sat, 01 Mar 2008 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598733</guid>        </item>
        <item>
            <title>Approaches to dimensionality reduction in proteomic biomarker studies.</title>
            <link>http://www.medworm.com/index.php?rid=1598732&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18310106%26dopt%3DAbstract</link>
            <description>This article reviews dimensionality reduction methods that have been used in proteomic biomarker studies. It then focuses on the problem of selecting the most appropriate method for a specific task or dataset, and proposes method combination as a potential alternative to single-method selection. Finally, it points out the potential of novel dimension reduction techniques, in particular those that incorporate domain knowledge through the use of informative priors or causal inference.
    PMID: 18310106 [PubMed - indexed for MEDLINE] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598732</comments>
            <pubDate>Sat, 01 Mar 2008 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598732</guid>        </item>
        <item>
            <title>Classification of mass-spectrometric data in clinical proteomics using learning vector quantization methods.</title>
            <link>http://www.medworm.com/index.php?rid=1598730&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18334515%26dopt%3DAbstract</link>
            <description>Authors: Villmann T, Schleif FM, Kostrzewa M, Walch A, Hammer B
    In the present contribution we propose two recently developed classification algorithms for the analysis of mass-spectrometric data-the supervised neural gas and the fuzzy-labeled self-organizing map. The algorithms are inherently regularizing, which is recommended, for these spectral data because of its high dimensionality and the sparseness for specific problems. The algorithms are both prototype-based such that the principle of characteristic representants is realized. This leads to an easy interpretation of the generated classifcation model. Further, the fuzzy-labeled self-organizing map is able to process uncertainty in data, and classification results can be obtained as fuzzy decisions. Moreover, this fuzzy classific...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598730</comments>
            <pubDate>Sat, 01 Mar 2008 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598730</guid>        </item>
        <item>
            <title>Algorithms and tools for analysis and management of mass spectrometry data.</title>
            <link>http://www.medworm.com/index.php?rid=1598728&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18356204%26dopt%3DAbstract</link>
            <description>Authors: Veltri P
    Mass spectrometry (MS) is a technique that is used for biological studies. It consists in associating a spectrum to a biological sample. A spectrum consists of couples of values (intensity, m/z), where intensity measures the abundance of biomolecules (as proteins) with a mass-to-charge ratio (m/z) present in the originating sample. In proteomics experiments, MS spectra are used to identify pattern expressions in clinical samples that may be responsible of diseases. Recently, to improve the identification of peptides/proteins related to patterns, MS/MS process is used, consisting in performing cascade of mass spectrometric analysis on selected peaks. Latter technique has been demonstrated to improve the identification and quantification of proteins/peptide in samples. ...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598728</comments>
            <pubDate>Sat, 01 Mar 2008 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598728</guid>        </item>
        <item>
            <title>Biobanking for Europe.</title>
            <link>http://www.medworm.com/index.php?rid=1598751&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17959611%26dopt%3DAbstract</link>
            <description>Authors: Yuille M, van Ommen GJ, Br&amp;#xE9;chot C, Cambon-Thomsen A, Dagher G, Landegren U, Litton JE, Pasterk M, Peltonen L, Taussig M, Wichmann HE, Zatloukal K
    Biobanks are well-organized resources comprising biological samples and associated information that are accessible to scientific investigation. Across Europe, millions of samples with related data are held in different types of collections. While individual collections can be well organized and accessible, the resources are subject to fragmentation, insecurity of funding and incompleteness. To address these issues, a Biobanking and BioMolecular Resources Infrastructure (BBMRI) is to be developed across Europe, thereby implementing a European 'roadmap' for research infrastructures that was developed by a forum of EU member states...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598751</comments>
            <pubDate>Tue, 01 Jan 2008 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598751</guid>        </item>
        <item>
            <title>Correlated substitution analysis and the prediction of amino acid structural contacts.</title>
            <link>http://www.medworm.com/index.php?rid=1598749&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18000015%26dopt%3DAbstract</link>
            <description>Authors: Horner DS, Pirovano W, Pesole G
    It has long been suspected that analysis of correlated amino acid substitutions should uncover pairs or clusters of sites that are spatially proximal in mature protein structures. Accordingly, methods based on different mathematical principles such as information theory, correlation coefficients and maximum likelihood have been developed to identify co-evolving amino acids from multiple sequence alignments. Sets of pairs of sites whose behaviour is identified by these methods as correlated are often significantly enriched in pairs of spatially proximal residues. However, relatively high levels of false-positive predictions typically render such methods, in isolation, of little use in the ab initio prediction of protein structure. Misleading sign...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598749</comments>
            <pubDate>Tue, 01 Jan 2008 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598749</guid>        </item>
        <item>
            <title>Current trends in the bioinformatic sequence analysis of metabolic pathways in prokaryotes.</title>
            <link>http://www.medworm.com/index.php?rid=1598747&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18024984%26dopt%3DAbstract</link>
            <description>Authors: Brilli M, Fani R, Li&amp;#xF2; P
    The study of metabolic pathways is becoming increasingly important to exploit an integrated, systems-level approach for optimizing a desired cellular property or phenotype. In this context, the integration of genomics data with genetic, metabolic and regulatory models is essential because the systematic design of artificial, biological systems requires the identification of robust building blocks like gene promoters, metabolic pathways or genetic circuits taken from natural organisms, and manipulated to develop ad hoc features. Computational tools allowing precise descriptions of natural pathways might thus allow improving the performance of artificial routes. In this review, we introduce the most recent bioinformatics tools enabling detailed chara...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598747</comments>
            <pubDate>Tue, 01 Jan 2008 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598747</guid>        </item>
        <item>
            <title>Automation of in-silico data analysis processes through workflow management systems.</title>
            <link>http://www.medworm.com/index.php?rid=1598746&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18056132%26dopt%3DAbstract</link>
            <description>Authors: Romano P
    Data integration is needed in order to cope with the huge amounts of biological information now available and to perform data mining effectively. Current data integration systems have strict limitations, mainly due to the number of resources, their size and frequency of updates, their heterogeneity and distribution on the Internet. Integration must therefore be achieved by accessing network services through flexible and extensible data integration and analysis network tools. EXtensible Markup Language (XML), Web Services and Workflow Management Systems (WMS) can support the creation and deployment of such systems. Many XML languages and Web Services for bioinformatics have already been designed and implemented and some WMS have been proposed. In this article, we revie...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598746</comments>
            <pubDate>Tue, 01 Jan 2008 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598746</guid>        </item>
        <item>
            <title>Extensible open source content management systems and frameworks: a solution for many needs of a bioinformatics group.</title>
            <link>http://www.medworm.com/index.php?rid=1598745&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18057072%26dopt%3DAbstract</link>
            <description>Authors: Mooney SD, Baenziger PH
    A common challenge for bioinformaticians, in either academic or industry laboratory environments, is providing informatic solutions via the Internet or through a web browser. Recently, the open source community began developing tools for building and maintaining web applications for many disciplines. These content management systems (CMS) provide many of the basic needs of an informatics group, whether in a small company, a group within a larger organisation or an academic laboratory. These tools aid in managing software development, website development, document development, course development, datasets, collaborations and customers. Since many of these tools are extensible, they can be developed to support other research-specific activities, such as h...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598745</comments>
            <pubDate>Tue, 01 Jan 2008 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598745</guid>        </item>
        <item>
            <title>An overview of image-processing methods for Affymetrix GeneChips.</title>
            <link>http://www.medworm.com/index.php?rid=1598744&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18057073%26dopt%3DAbstract</link>
            <description>We present an overview of image-processing methods for Affymetrix GeneChips. All GeneChips are affected to some extent by spatially coherent defects and image processing has a number of potential impacts on the downstream analysis of GeneChip data. Fortunately, there are now a number of robust and accurate algorithms, which identify the most disabling defects. One group of algorithms concentrate on the transformation from the original hybridisation DAT image to the representative CEL file. Another set uses dedicated pattern recognition routines to detect different types of hybridisation defect in replicates. A third type exploits the information provided by public repositories of GeneChips (such as GEO). The use of these algorithms improves the sensitivity of GeneChips, and should be a pre...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598744</comments>
            <pubDate>Tue, 01 Jan 2008 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598744</guid>        </item>
        <item>
            <title>Biomedical ontologies: a functional perspective.</title>
            <link>http://www.medworm.com/index.php?rid=1598742&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18077472%26dopt%3DAbstract</link>
            <description>The objective of this review is to give an overview of biomedical ontology in practical terms by providing a functional perspective--describing how bio-ontologies can and are being used. As biomedical scientists begin to recognize the many different ways ontologies enable biomedical research, they will drive the emergence of new computer applications that will help them exploit the wealth of research data now at their fingertips.
    PMID: 18077472 [PubMed - indexed for MEDLINE] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598742</comments>
            <pubDate>Tue, 01 Jan 2008 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598742</guid>        </item>
        <item>
            <title>Three lectures on case-control genetic association analysis.</title>
            <link>http://www.medworm.com/index.php?rid=1598741&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18083722%26dopt%3DAbstract</link>
            <description>Authors: Li W
    The purpose of this review is to focus on the three most important themes in genetic association studies using randomly selected patients (case, affected) and normal samples (control, unaffected), so that students and researchers alike who are new to this field may quickly grasp the key issues and command basic analysis methods. These three themes are: elementary categorical analysis; disease mutation as an unobserved entity; and the importance of homogeneity in genetic association analysis.
    PMID: 18083722 [PubMed - indexed for MEDLINE] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598741</comments>
            <pubDate>Tue, 01 Jan 2008 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598741</guid>        </item>
        <item>
            <title>A practical guide to the art of RNA gene prediction.</title>
            <link>http://www.medworm.com/index.php?rid=1598781&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17483123%26dopt%3DAbstract</link>
            <description>Authors: Meyer IM
    This review introduces the different strategies and computational methods that can be used in order to predict RNA genes. It discusses our current view of RNA genes as well as recent computational analyses of RNA genes and concludes with an outlook to future directions in algorithm development and data analyses.
    PMID: 17483123 [PubMed - indexed for MEDLINE] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598781</comments>
            <pubDate>Thu, 01 Nov 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598781</guid>        </item>
        <item>
            <title>High-throughput modeling and analysis of protein structural dynamics.</title>
            <link>http://www.medworm.com/index.php?rid=1598780&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17485424%26dopt%3DAbstract</link>
            <description>Authors: Liu X, Karimi HA
    Protein function is a dynamic property closely related to the conformational mechanisms of protein structure in its physiological environment. To understand and control the function of target proteins, it becomes increasingly important to develop methods and tools for predicting collective motions at the molecular level. In this article, we review computational methods for predicting conformational dynamics and discuss software tools for data analysis. In particular, we discuss a high-throughput, web-based system called iGNM for protein structural dynamics. iGNM contains a database of protein motions for more than 20 000 PDB structures and supports online calculations for newly deposited PDB structures or user-modified structures. iGNM allows dynamics analysis...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598780</comments>
            <pubDate>Thu, 01 Nov 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598780</guid>        </item>
        <item>
            <title>Statistical software for gene mapping by admixture linkage disequilibrium.</title>
            <link>http://www.medworm.com/index.php?rid=1598762&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17640923%26dopt%3DAbstract</link>
            <description>Authors: Montana G, Hoggart C
    Admixture mapping is a statistical methodology that detects genetic variants in recently admixed populations that are responsible for ethnic differences in disease risk. Three software packages are now available for admixture mapping and we provide a brief overview of the statistical methods and other principal features they implement.
    PMID: 17640923 [PubMed - indexed for MEDLINE] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598762</comments>
            <pubDate>Thu, 01 Nov 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598762</guid>        </item>
        <item>
            <title>BioManager: the use of a bioinformatics web application as a teaching tool in undergraduate bioinformatics training.</title>
            <link>http://www.medworm.com/index.php?rid=1598758&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17715151%26dopt%3DAbstract</link>
            <description>Authors: Cattley S, Arthur JW
    The completion of the human genome project, and other genome sequencing projects, has spearheaded the emergence of the field of bioinformatics. Using computer programs to analyse DNA and protein information has become an important area of life science research and development. While it is not necessary for most life science researchers to develop specialist bioinformatic skills (including software development), basic skills in the application of common bioinformatics software and the effective interpretation of results are increasingly required by all life science researchers. Training in bioinformatics is increasingly occurring within the university system as part of existing undergraduate science and specialist degrees. One difficulty in bioinformatics e...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598758</comments>
            <pubDate>Thu, 01 Nov 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598758</guid>        </item>
        <item>
            <title>A microarray analysis for differential gene expression in the soybean genome using Bioconductor and R.</title>
            <link>http://www.medworm.com/index.php?rid=1598754&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17906332%26dopt%3DAbstract</link>
            <description>This article describes specific procedures for conducting quality assessment of Affymetrix GeneChip(R) soybean genome data and for performing analyses to determine differential gene expression using the open-source R programming environment in conjunction with the open-source Bioconductor software. We describe procedures for extracting those Affymetrix probe set IDs related specifically to the soybean genome on the Affymetrix soybean chip and demonstrate the use of exploratory plots including images of raw probe-level data, boxplots, density plots and M versus A plots. RNA degradation and recommended procedures from Affymetrix for quality control are discussed. An appropriate probe-level model provides an excellent quality assessment tool. To demonstrate this, we discuss and display chip p...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598754</comments>
            <pubDate>Thu, 01 Nov 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598754</guid>        </item>
        <item>
            <title>Discovering and detecting transposable elements in genome sequences.</title>
            <link>http://www.medworm.com/index.php?rid=1598753&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17932080%26dopt%3DAbstract</link>
            <description>Authors: Bergman CM, Quesneville H
    The contribution of transposable elements (TEs) to genome structure and evolution as well as their impact on genome sequencing, assembly, annotation and alignment has generated increasing interest in developing new methods for their computational analysis. Here we review the diversity of innovative approaches to identify and annotate TEs in the post-genomic era, covering both the discovery of new TE families and the detection of individual TE copies in genome sequences. These approaches span a broad spectrum in computational biology including de novo, homology-based, structure-based and comparative genomic methods. We conclude that the integration and visualization of multiple approaches and the development of new conceptual representations for TE ann...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598753</comments>
            <pubDate>Thu, 01 Nov 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598753</guid>        </item>
        <item>
            <title>Informatics in neuroscience.</title>
            <link>http://www.medworm.com/index.php?rid=1598752&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17932081%26dopt%3DAbstract</link>
            <description>Authors: French L, Pavlidis P
    The application of informatics to neuroscience goes far beyond 'traditional' bioinformatics modalities such as DNA sequences. In this review, we describe how informatics is being used to study the nervous system at multiple levels, spanning scales from molecules to behavior. The continuing development of standards for data exchange and interoperability, together with increasing awareness and acceptance of the importance of data sharing, are among the key efforts required to advance the field.
    PMID: 17932081 [PubMed - indexed for MEDLINE] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598752</comments>
            <pubDate>Thu, 01 Nov 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598752</guid>        </item>
        <item>
            <title>Manuscript Central interactive online system and issue summary.</title>
            <link>http://www.medworm.com/index.php?rid=1598748&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18024470%26dopt%3DAbstract</link>
            <description>Authors: Bishop MJ
    
    PMID: 18024470 [PubMed - indexed for MEDLINE] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598748</comments>
            <pubDate>Thu, 01 Nov 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598748</guid>        </item>
        <item>
            <title>Current trends in computational inference from mass spectrometry-based proteomics.</title>
            <link>http://www.medworm.com/index.php?rid=1598771&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17584764%26dopt%3DAbstract</link>
            <description>Authors: Webb-Robertson BJ, Cannon WR
    Mass spectrometry offers a high-throughput approach to quantifying the proteome associated with a biological sample and hence has become the primary approach of proteomic analyses. Computation is tightly coupled to this advanced technological platform as a required component of not only peptide and protein identification, but quantification and functional inference, such as protein modifications and interactions. Proteomics faces several key computational challenges such as identification of proteins and peptides from tandem mass spectra as well as their quantitation. In addition, the application of proteomics to systems biology requires understanding the functional proteome, including how the dynamics of the cell change in response to protein modi...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598771</comments>
            <pubDate>Sat, 01 Sep 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598771</guid>        </item>
        <item>
            <title>Informatics challenges in structured RNA.</title>
            <link>http://www.medworm.com/index.php?rid=1598769&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17611237%26dopt%3DAbstract</link>
            <description>Authors: Laederach A
    The world of regulatory RNAs is fast expanding into mainstream molecular biology as both a subject of intense mechanistic study and as a tool for functional characterization. The RNA world is one of complex structures that carry out catalysis, sense metabolites and synthesize proteins. The dynamic and structural nature of RNAs presents a whole new set of informatics challenges to the computational community. The ability to relate structure and dynamics to function will be key to understanding this complex world. I review several important classes of structured RNAs that present our community with a series of biologically novel informatics challenges. I also review available informatics tools that have been recently developed in the field.
    PMID: 17611237 [PubMed...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598769</comments>
            <pubDate>Sat, 01 Sep 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598769</guid>        </item>
        <item>
            <title>Current progress in computational metabolomics.</title>
            <link>http://www.medworm.com/index.php?rid=1598768&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17626065%26dopt%3DAbstract</link>
            <description>Authors: Wishart DS
    Being a relatively new addition to the 'omics' field, metabolomics is still evolving its own computational infrastructure and assessing its own computational needs. Due to its strong emphasis on chemical information and because of the importance of linking that chemical data to biological consequences, metabolomics must combine elements of traditional bioinformatics with traditional cheminformatics. This is a significant challenge as these two fields have evolved quite separately and require very different computational tools and skill sets. This review is intended to familiarize readers with the field of metabolomics and to outline the needs, the challenges and the recent progress being made in four areas of computational metabolomics: (i) metabolomics databases; (...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598768</comments>
            <pubDate>Sat, 01 Sep 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598768</guid>        </item>
        <item>
            <title>Protein interactions and disease: computational approaches to uncover the etiology of diseases.</title>
            <link>http://www.medworm.com/index.php?rid=1598764&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17638813%26dopt%3DAbstract</link>
            <description>Authors: Kann MG
    The genomic era has been characterised by vast amounts of data from diverse sources, creating a need for new tools to extract biologically meaningful information. Bioinformatics is, for the most part, responding to that need. The sparseness of the genomic data associated with diseases, however, creates a new challenge. Understanding the complex interplay between genes and proteins requires integration of data from a wide variety of sources, i.e. gene expression, genetic linkage, protein interaction, and protein structure among others. Thus, computational tools have become critical for the integration, representation and visualization of heterogeneous biomedical data. Furthermore, several bioinformatics methods have been developed to formulate predictions about the func...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598764</comments>
            <pubDate>Sat, 01 Sep 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598764</guid>        </item>
        <item>
            <title>Biodiversity informatics: organizing and linking information across the spectrum of life.</title>
            <link>http://www.medworm.com/index.php?rid=1598759&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17704120%26dopt%3DAbstract</link>
            <description>Authors: Sarkar IN
    Biological knowledge can be inferred from three major levels of information: molecules, organisms and ecologies. Bioinformatics is an established field that has made significant advances in the development of systems and techniques to organize contemporary molecular data; biodiversity informatics is an emerging discipline that strives to develop methods to organize knowledge at the organismal level extending back to the earliest dates of recorded natural history. Furthermore, while bioinformatics studies generally focus on detailed examinations of key 'model' organisms, biodiversity informatics aims to develop over-arching hypotheses that span the entire tree of life. Biodiversity informatics is presented here as a discipline that unifies biological information from ...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598759</comments>
            <pubDate>Sat, 01 Sep 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598759</guid>        </item>
        <item>
            <title>Current progress in bioinformatics 2007.</title>
            <link>http://www.medworm.com/index.php?rid=1598757&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17724063%26dopt%3DAbstract</link>
            <description>Authors: Altman RB
    
    PMID: 17724063 [PubMed - indexed for MEDLINE] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598757</comments>
            <pubDate>Sat, 01 Sep 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598757</guid>        </item>
        <item>
            <title>Current progress in network research: toward reference networks for key model organisms.</title>
            <link>http://www.medworm.com/index.php?rid=1598756&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17728341%26dopt%3DAbstract</link>
            <description>Authors: Srinivasan BS, Shah NH, Flannick JA, Abeliuk E, Novak AF, Batzoglou S
    The collection of multiple genome-scale datasets is now routine, and the frontier of research in systems biology has shifted accordingly. Rather than clustering a single dataset to produce a static map of functional modules, the focus today is on data integration, network alignment, interactive visualization and ontological markup. Because of the intrinsic noisiness of high-throughput measurements, statistical methods have been central to this effort. In this review, we briefly survey available datasets in functional genomics, review methods for data integration and network alignment, and describe recent work on using network models to guide experimental validation. We explain how the integration and validat...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598756</comments>
            <pubDate>Sat, 01 Sep 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598756</guid>        </item>
        <item>
            <title>Frontiers of biomedical text mining: current progress.</title>
            <link>http://www.medworm.com/index.php?rid=1598750&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17977867%26dopt%3DAbstract</link>
            <description>Authors: Zweigenbaum P, Demner-Fushman D, Yu H, Cohen KB
    It is now almost 15 years since the publication of the first paper on text mining in the genomics domain, and decades since the first paper on text mining in the medical domain. Enormous progress has been made in the areas of information retrieval, evaluation methodologies and resource construction. Some problems, such as abbreviation-handling, can essentially be considered solved problems, and others, such as identification of gene mentions in text, seem likely to be solved soon. However, a number of problems at the frontiers of biomedical text mining continue to present interesting challenges and opportunities for great improvements and interesting research. In this article we review the current state of the art in biomedical t...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598750</comments>
            <pubDate>Sat, 01 Sep 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598750</guid>        </item>
        <item>
            <title>Combining experiments with multi-cell agent-based modeling to study biological tissue patterning.</title>
            <link>http://www.medworm.com/index.php?rid=1598772&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17584763%26dopt%3DAbstract</link>
            <description>Authors: Thorne BC, Bailey AM, Peirce SM
    Agent-based modeling (ABM), also termed 'Individual-based modeling (IBM)', is a computational approach that simulates the interactions of autonomous entities (agents, or individual cells) with each other and their local environment to predict higher level emergent patterns. A literature-derived rule set governs the actions of each individual agent. While this technique has been widely used in the ecological and social sciences, it has only recently been applied in biomedical research. The purpose of this review is to provide an introduction to ABM as it has been used to study complex multi-cell biological phenomena, underscore the importance of coupling models with experimental work, and outline future challenges for the ABM field and its applic...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598772</comments>
            <pubDate>Sun, 01 Jul 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598772</guid>        </item>
        <item>
            <title>An integrative approach to understanding mechanosensation.</title>
            <link>http://www.medworm.com/index.php?rid=1598770&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17591637%26dopt%3DAbstract</link>
            <description>Authors: Poirier CC, Iglesias PA
    The ability for a living organism to sense and respond to its external environment is crucial to its survival. Understanding mechanosensation, the mechanism by which organisms react in response to mechanical stimuli, presents many interesting and challenging problems for both experimental and computational biologists. A major difficulty in studying mechanosensors is their inherent multiscale nature. The systems involved in mechanosesnsing can span eight orders of magnitude in length scale and up to 10 orders of magnitude in time scale. Trying to ascertain information across these length and time scales simultaneously is challenging. This problem has led to the need to approach these types of problems using an integrative approach, combining both computa...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598770</comments>
            <pubDate>Sun, 01 Jul 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598770</guid>        </item>
        <item>
            <title>Petri net modelling of biological networks.</title>
            <link>http://www.medworm.com/index.php?rid=1598767&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17626066%26dopt%3DAbstract</link>
            <description>This article intends to present the basics of the approach and to foster the potential role PNs could play in the development of the computational systems biology.
    PMID: 17626066 [PubMed - indexed for MEDLINE] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598767</comments>
            <pubDate>Sun, 01 Jul 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598767</guid>        </item>
        <item>
            <title>Dynamical roles of biological regulatory circuits.</title>
            <link>http://www.medworm.com/index.php?rid=1598766&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17626067%26dopt%3DAbstract</link>
            <description>Authors: Thieffry D
    Regulatory circuits are found at the basis of all non-trivial dynamical properties of biological networks. More specifically, positive circuits are involved in the generation of multiple differentiated states, whereas negative circuits can generate cyclic or homeostatic behaviours. These notions are briefly reviewed, from initial biological formulations to mathematical formalisations, further encompassing their application to the design of synthetic regulatory systems. Finally, current challenges for the analysis of increasingly complex regulatory networks are indicated, as well as prospects for our understanding of development and evolution.
    PMID: 17626067 [PubMed - indexed for MEDLINE] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598766</comments>
            <pubDate>Sun, 01 Jul 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598766</guid>        </item>
        <item>
            <title>Combined experimental and computational approaches to study the regulatory elements in eukaryotic genes.</title>
            <link>http://www.medworm.com/index.php?rid=1598765&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17627963%26dopt%3DAbstract</link>
            <description>This article provides short review of approaches to computational recognition of TFBS in genomic sequences and methods of experimental verification of predicted sites. We also present a case study of the interplay between experimental and theoretical approaches to the successful prediction of Steroidogenic Factor 1 (SF1).
    PMID: 17627963 [PubMed - indexed for MEDLINE] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598765</comments>
            <pubDate>Sun, 01 Jul 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598765</guid>        </item>
        <item>
            <title>Integrative biology--the way forward.</title>
            <link>http://www.medworm.com/index.php?rid=1598763&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17640922%26dopt%3DAbstract</link>
            <description>Authors: Hodgman C
    
    PMID: 17640922 [PubMed - indexed for MEDLINE] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598763</comments>
            <pubDate>Sun, 01 Jul 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598763</guid>        </item>
        <item>
            <title>Towards a calculus of biomolecular complexes at equilibrium.</title>
            <link>http://www.medworm.com/index.php?rid=1598761&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17640924%26dopt%3DAbstract</link>
            <description>Authors: Mjolsness E
    An overview is presented of the construction and use of algebraic partition functions to represent the equilibrium statistical mechanics of multimolecular complexes and their action within a larger regulatory network. Unlike many applications of equilibrium statistical mechanics, multimolecular complexes may operate with various subsets of their components present and connected to the others, the rest remaining in solution. Thus they are variable-structure systems. This aspect of their behavior may be accounted for by the use of 'fugacity' variables as a representation within the partition functions. Four principles are proposed by which the combinatorics of molecular complex construction can be reflected in the construction of their partition functions. The corres...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598761</comments>
            <pubDate>Sun, 01 Jul 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598761</guid>        </item>
        <item>
            <title>Modelling and simulation techniques for membrane biology.</title>
            <link>http://www.medworm.com/index.php?rid=1598760&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17693422%26dopt%3DAbstract</link>
            <description>Authors: Burrage K, Hancock J, Leier A, Nicolau DV
    One of the most important aspects of Computational Cell Biology is the understanding of the complicated dynamical processes that take place on plasma membranes. These processes are often so complicated that purely temporal models cannot always adequately capture the dynamics. On the other hand, spatial models can have large computational overheads. In this article, we review some of these issues with respect to chemistry, membrane microdomains and anomalous diffusion and discuss how to select appropriate modelling and simulation paradigms based on some or all the following aspects: discrete, continuous, stochastic, delayed and complex spatial processes.
    PMID: 17693422 [PubMed - indexed for MEDLINE] (Source: Briefings in Bioinformat...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598760</comments>
            <pubDate>Sun, 01 Jul 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598760</guid>        </item>
        <item>
            <title>Knowledge Integration in Biomedicine: Technology and Community.</title>
            <link>http://www.medworm.com/index.php?rid=1598774&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17526592%26dopt%3DAbstract</link>
            <description>Authors: Clark T
    
    PMID: 17526592 [PubMed - as supplied by publisher] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598774</comments>
            <pubDate>Fri, 25 May 2007 04:00:00 +0100</pubDate>
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        <item>
            <title>Boca: an open-source RDF store for building Semantic Web applications.</title>
            <link>http://www.medworm.com/index.php?rid=1598779&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17491005%26dopt%3DAbstract</link>
            <description>This article presents the design goals and features of the open-source Boca RDF server in the context of a community of cancer-tumor modeling investigators. Boca supplements the desirable data features of the Semantic Web with important enterprise and application features to power a new generation of Semantic-Web-based applications. The data features enable the integration and retrieval of tremendous quantities of diverse data. The enterprise features promote data integrity, fidelity, provenance and robustness. The application features provide for collaborative applications and dynamic user interfaces.
    PMID: 17491005 [PubMed - indexed for MEDLINE] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598779</comments>
            <pubDate>Tue, 01 May 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598779</guid>        </item>
        <item>
            <title>Using provenance to manage knowledge of in silico experiments.</title>
            <link>http://www.medworm.com/index.php?rid=1598778&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17502335%26dopt%3DAbstract</link>
            <description>This article offers a briefing in one of the knowledge management issues of in silico experimentation in bioinformatics. Recording of the provenance of an experiment-what was done; where, how and why, etc. is an important aspect of scientific best practice that should be extended to in silico experimentation. We will do this in the context of eScience which has been part of the move of bioinformatics towards an industrial setting. Despite the computational nature of bioinformatics, these analyses are scientific and thus necessitate their own versions of typical scientific rigour. Just as recording who, what, why, when, where and how of an experiment is central to the scientific process in laboratory science, so it should be in silico science. The generation and recording of these aspects, ...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598778</comments>
            <pubDate>Tue, 01 May 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598778</guid>        </item>
        <item>
            <title>Knowledge networks in the age of the Semantic Web.</title>
            <link>http://www.medworm.com/index.php?rid=1598777&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17502336%26dopt%3DAbstract</link>
            <description>Authors: Neumann E, Prusak L
    The Web has become the major medium for various communities to share their knowledge. To this end, it provides an optimal environment for knowledge networks. The web offers global connectivity that is virtually instantaneous, and whose resources and documents can easily be indexed for easy searching. In the coupled realms of biomedical research and healthcare, this has become especially important where today many thousands of communities already exist that connect across academia, hospitals and industry. These communities also rely on several forms of knowledge assets, including publications, experimental data, domain-specific vocabularies and policies. Web-based communities will be one of the earlier beneficiaries of the emerging Semantic Web. With the new...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598777</comments>
            <pubDate>Tue, 01 May 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598777</guid>        </item>
        <item>
            <title>SenseLab: new developments in disseminating neuroscience information.</title>
            <link>http://www.medworm.com/index.php?rid=1598776&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17510162%26dopt%3DAbstract</link>
            <description>This article presents the latest developments in neuroscience information dissemination through the SenseLab suite of databases: NeuronDB, CellPropDB, ORDB, OdorDB, OdorMapDB, ModelDB and BrainPharm. These databases include information related to: (i) neuronal membrane properties and neuronal models, and (ii) genetics, genomics, proteomics and imaging studies of the olfactory system. We describe here: the new features for each database, the evolution of SenseLab's unifying database architecture and instances of SenseLab database interoperation with other neuroscience online resources.
    PMID: 17510162 [PubMed - indexed for MEDLINE] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598776</comments>
            <pubDate>Tue, 01 May 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598776</guid>        </item>
        <item>
            <title>Alzforum and SWAN: the present and future of scientific web communities.</title>
            <link>http://www.medworm.com/index.php?rid=1598775&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17510163%26dopt%3DAbstract</link>
            <description>Authors: Clark T, Kinoshita J
    Scientists drove the early development of the World Wide Web, primarily as a means for rapid communication, document sharing and data access. They have been far slower to adopt the web as a medium for building research communities. Yet, web-based communities hold great potential for accelerating the pace of scientific research. In this article, we will describe the 10-year experience of the Alzheimer Research Forum ('Alzforum'), a unique example of a thriving scientific web community, and explain the features that contributed to its success. We will then outline the SWAN (Semantic Web Applications in Neuromedicine) project, in which Alzforum curators are collaborating with informatics researchers to develop novel approaches that will enable communities to ...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598775</comments>
            <pubDate>Tue, 01 May 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598775</guid>        </item>
        <item>
            <title>Improving life sciences information retrieval using semantic web technology.</title>
            <link>http://www.medworm.com/index.php?rid=1598773&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17526593%26dopt%3DAbstract</link>
            <description>This article gives an overview of the principles underlying a Semantic Web-enabled information retrieval system: creating a unified abstraction for knowledge using the RDF semantic network model; designing semantic lenses that extract contextually relevant subsets of information; and assembling semantic lenses into powerful information displays. Furthermore, concrete examples of how these principles can be applied to life science problems including a scenario involving a drug discovery dashboard prototype called BioDash are provided.
    PMID: 17526593 [PubMed - indexed for MEDLINE] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598773</comments>
            <pubDate>Tue, 01 May 2007 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598773</guid>        </item>
        <item>
            <title>The WWWH of remote homolog detection: the state of the art.</title>
            <link>http://www.medworm.com/index.php?rid=1598796&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17003074%26dopt%3DAbstract</link>
            <description>Authors: Fariselli P, Rossi I, Capriotti E, Casadio R
    The detection of remote homolog pairs of proteins using computational methods is a pivotal problem in structural bioinformatics, aiming to compute protein folds on the basis of information in the database of known structures. In the last 25 years, several methods have been developed to tackle this problem, based on different approaches including sequence-sequence alignments and/or structure comparison. In this article, we will briefly discuss When, Why, Where and How (WWWH) to perform remote homology search, reviewing some of the most widely adopted computational approaches. The specific aim is highlighting the basic criteria implemented by different research groups and commenting on the status of the art as well as on still-open qu...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598796</comments>
            <pubDate>Thu, 01 Mar 2007 05:00:00 +0100</pubDate>
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        <item>
            <title>Methods and protocols for prediction of immunogenic epitopes.</title>
            <link>http://www.medworm.com/index.php?rid=1598793&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17077136%26dopt%3DAbstract</link>
            <description>This article examines existing computational strategies for the study of peptide/MHC interactions. The most important bioinformatics tools and methods with relevance to the study of peptide/MHC interactions have been reviewed. We have also provided guidelines for predicting antigenic peptides based on the availability of existing experimental data.
    PMID: 17077136 [PubMed - indexed for MEDLINE] (Source: Briefings in Bioinformatics)</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598793</comments>
            <pubDate>Thu, 01 Mar 2007 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">1598793</guid>        </item>
        <item>
            <title>Enrichment analysis in high-throughput genomics - accounting for dependency in the NULL.</title>
            <link>http://www.medworm.com/index.php?rid=1598792&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17077137%26dopt%3DAbstract</link>
            <description>Authors: Gold DL, Coombes KR, Wang J, Mallick B
    Translating the overwhelming amount of data generated in high-throughput genomics experiments into biologically meaningful evidence, which may for example point to a series of biomarkers or hint at a relevant pathway, is a matter of great interest in bioinformatics these days. Genes showing similar experimental profiles, it is hypothesized, share biological mechanisms that if understood could provide clues to the molecular processes leading to pathological events. It is the topic of further study to learn if or how a priori information about the known genes may serve to explain coexpression. One popular method of knowledge discovery in high-throughput genomics experiments, enrichment analysis (EA), seeks to infer if an interesting collect...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=1598792</comments>
            <pubDate>Thu, 01 Mar 2007 05:00:00 +0100</pubDate>
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        <item>
            <title>Evolving research trends in bioinformatics.</title>
            <link>http://www.medworm.com/index.php?rid=1598791&amp;cid=s_37630_79_f&amp;fid=37630&amp;url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D17077138%26dopt%3DAbstract</link>
            <description>Authors: Perez-Iratxeta C, Andrade-Navarro MA, Wren JD
    The cross-disciplinary nature of bioinformatics entails co-evolution with other biomedical disciplines, whereby some bioinformatics applications become popular in certain disciplines and, in turn, these disciplines influence the focus of future bioinformatics development efforts. We observe here that the growth of computational approaches within various biomedical disciplines is not merely a reflection of a general extended usage of computers and the Internet, but due to the production of useful bioinformatics databases and methods for the rest of the biomedical scientific community. We have used the abstracts stored both in the MEDLINE database of biomedical literature and in NIH-funded project grants, to quantify two effects. Fir...</description>
            <author>Briefings in Bioinformatics</author>
            <type>journals</type>
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            <pubDate>Thu, 01 Mar 2007 05:00:00 +0100</pubDate>
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