MedWorm: Bioinformatics

Automatic Clustering of Flow Cytometry Data with Density-Based Merging

Advances in Bioinformatics — Thu, 19 Nov 2009 16:18:58 +0100

We describe methodology and software to automatically identify cell populations in flow cytometry data. Our approach advances the paradigm of manually gating sequential two-dimensional projections of the data to a procedure that automatically produces gates based on statistical theory. Our approach is nonparametric and can reproduce nonconvex subpopulations that are known to occur in flow cytometry samples, but which cannot be produced with current parametric model-based approaches. We illustrate the methodology with a sample of mouse spleen and peritoneal cavity cells. (Source: Advances in Bioinformatics)

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SitesIdentify: a protein functional site prediction tool

BMC Bioinformatics - Latest articles — Wed, 18 Nov 2009 00:00:00 +0100

Conclusions: SitesIdentify is able to produce comparable accuracy in predicting functional sites to its closest available counterpart, but in addition achieves improved accuracy for proteins with few characterised homologues. SitesIdentify is available via a webserver at www.manchester.ac.uk/bioinformatics/sitesidentify/ (Source: BMC Bioinformatics - Latest articles)

The ontology of biological sequences

BMC Bioinformatics - Latest articles — Wed, 18 Nov 2009 00:00:00 +0100

Conclusions: Axioms are necessary to achieve the main goal of ontologies: to formally specify the meaning of terms used within a domain. The axiom system for the ontology of biological sequences is the first elaborate axiom system for an OBO Foundry ontology and can serve as starting point for the development of more formal ontologies and ultimately of knowledge-based applications. (Source: BMC Bioinformatics - Latest articles)

Nonlinear preprocessing method for detecting peaks from gas chromatograms

BMC Bioinformatics - Latest articles — Wed, 18 Nov 2009 00:00:00 +0100

Conclusions: Our results demonstrate that the proposed method can achieve near perfect peak detection performance while maintaining very small false alarm probabilities in case of gas chromatograms. Given the fact that biological signals appear in the form of peaks in various experimental data and that the propose method can easily be extended to such data, our approach will be a useful and robust tool that can help researchers highlight valid signals in their noisy measurements. (Source: BMC Bioinformatics - Latest articles)

Fluorescence Intensity Normalisation: Correcting for Time Effects in Large-Scale Flow Cytometric Analysis

Advances in Bioinformatics — Tue, 17 Nov 2009 16:26:51 +0100

A next step to interpret the findings generated by genome-wide association studies is to associate molecular quantitative traits with disease-associated alleles. To this end, researchers are linking disease risk alleles with gene expression quantitative trait loci (eQTL). However, gene expression at the mRNA level is only an intermediate trait and flow cytometry analysis can provide more downstream and biologically valuable protein level information in multiple cell subsets simultaneously using freshly obtained samples. Because the throughput of flow cytometry is currently limited, experiments may need to span over several weeks or months to obtain a sufficient sample size to demonstrate genetic association. Therefore, normalisation methods are needed to control for technical variability a...

In response to 'Can sugars be produced from fatty acids? A test case for pathway analysis tools'

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

Motivation: In their article entitled ‘Can sugars be produced from fatty acids? A test case for pathway analysis tools’ de Figueiredo and co-authors assess the performance of three pathway prediction tools (METATOOL, PathFinding and Pathway Hunter Tool) using the synthesis of glucose-6-phosphate (G6P) from acetyl-CoA in humans as a test case. We think that this article is biased for three reasons: (i) the metabolic networks used as input for the respective tools were of very different sizes; (ii) the ‘assessment’ is restricted to two study cases; (iii) developers are inherently more skilled to use their own tools than those developed by other people. We extended the analyses led by de Figueiredo and clearly show that the apparent superior performance of their tool (...

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ncRNAppi--a tool for identifying disease-related miRNA and siRNA targeting pathways

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

Summary: Currently, there are a number of databases which store microRNA (miRNA) information, and tools available which provide miRNA target prediction. In this article, we describe a novel web-based tool that integrate the miRNA-targeted mRNA data, protein–protein interactions (PPI) records, tissues, biochemical pathways, human disease and gene function information to establish a disease-related miRNA target pathway database. This database is unique in the sense that it links miRNA target genes with their PPI partners according to being tissue- and diseases-specific or both. The same approach is also applied to siRNA data. This database provides two types of searches: (i) tissue- and (ii) disease-specific miRNA (or siRNA) targeting pathways. The search allows one to identify tissue-...

SimCT: a generic tool to visualize ontology-based relationships for biological objects

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

We present a web-based service, SimCT, which allows to graphically display the relationships between biological objects (e.g. genes or proteins) based on their annotations to a biomedical ontology. The result is presented as a tree of these objects, which can be viewed and explored through a specific java applet designed to highlight relevant features. Unlike the numerous tools that search for overrepresented terms, SimCT draws a simplified representation of biological terms present in the set of objects, and can be applied to any ontology for which annotation data is available. Being web-based, it does not require prior installation, and provides an intuitive, easy-to-use service. Availability: http://tagc.univ-mrs.fr/SimCT Contact: carl.herrmann@univmed.fr Supplementary information: Supp...

Client-side integration of life science literature resources

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

Motivation: The online resources in the life sciences are characterized by a great fragmentation and one of the pressing issues of bioinformatics is making the integration of these resources a smoother and more flexible process than it is currently. Here we present i-cite, a browser extension, which implements a client-side model of integration which improves the navigation within the rapidly increasing life science literature and links terms from it to corresponding non-textual data. Availability: http://i-cite.org. Contact: nan23@cam.ac.uk (Source: Bioinformatics)

W-ChIPMotifs: a web application tool for de novo motif discovery from ChIP-based high-throughput data

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

Summary: W-ChIPMotifs is a web application tool that provides a user friendly interface for de novo motif discovery. The web tool is based on our previous ChIPMotifs program which is a de novo motif finding tool developed for ChIP-based high-throughput data and incorporated various ab initio motif discovery tools such as MEME, MaMF, Weeder and optimized the significance of the detected motifs by using a bootstrap resampling statistic method and a Fisher test. Use of a randomized statistical model like bootstrap resampling can significantly increase the accuracy of the detected motifs. In our web tool, we have modified the program in two aspects: (i) we have refined the P-value with a Bonferroni correction; (ii) we have incorporated the STAMP tool to infer phylogenetic information and to de...

Processing and population genetic analysis of multigenic datasets with ProSeq3 software

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

Motivation: The current tendency in molecular population genetics is to use increasing numbers of genes in the analysis. Here I describe a program for handling and population genetic analysis of DNA polymorphism data collected from multiple genes. The program includes a sequence/alignment editor and an internal relational database that simplify the preparation and manipulation of multigenic DNA polymorphism datasets. The most commonly used DNA polymorphism analyses are implemented in ProSeq3, facilitating population genetic analysis of large multigenic datasets. Extensive input/output options make ProSeq3 a convenient hub for sequence data processing and analysis. Availability: The program is available free of charge from http://dps.plants.ox.ac.uk/sequencing/proseq.htm Contact: dmitry.fil...

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VDNA: The virtual DNA plug-in for VMD

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

Summary: The DNA inter base pair step parameters (Tilt, Roll, Twist, Shift, Slide, Rise) are a standard internal coordinate representation of DNA. In the absence of bend and shear, it is relatively easy to mentally visualize how Twist and Rise generate the familiar double helix. More complex structures do not readily yield to such intuition. For this reason, we developed a plug-in for VMD that accepts a set of mathematical expressions as input and generates a coarse-grained model of DNA as output. This feature of VDNA appears to provide a unique approach to DNA modeling. Predefined expressions include: linear, sheared, bent and circular DNA, and models of the nucleosome superhelix, chromatin, thermal motion and nucleosome unwrapping. Availability: VDNA is pre-installed in VMD, http://www.k...

EASYMIFS and SITEHOUND: a toolkit for the identification of ligand-binding sites in protein structures

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

Summary: SiteHound uses Molecular Interaction Fields (MIFs) produced by EasyMIFs to identify protein structure regions that show a high propensity for interaction with ligands. The type of binding site identified depends on the probe atom used in the MIF calculation. The input to EasyMIFs is a PDB file of a protein structure; the output MIF serves as input to SiteHound, which in turn produces a list of putative binding sites. Extensive testing of SiteHound for the detection of binding sites for drug-like molecules and phosphorylated ligands has been carried out. Availability: EasyMIFs and SiteHound executables for Linux, Mac OS X, and MS Windows operating systems are freely available for download from http://sitehound.sanchezlab.org/download.html. Contact: roberto@sanchezlab.org or roberto...

PoreLogo: a new tool to analyse, visualize and compare channels in transmembrane proteins

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

Summary: The increasing number of available atomic 3D structures of transmembrane channel proteins represents a valuable resource for better understanding their structure–function relationships and to eventually predict their selectivity. Herein, we present PoreLogo, an automatic tool for analysing, visualizing and comparing the amino acid composition of transmembrane channels and its conservation across the corresponding protein family. Availability: PoreLogo is accessible as a public web server at http://www.ebi.ac.uk/thornton-srv/software/PoreLogo/. Contacts: marial@ebi.ac.uk; romina.oliva@uniparthenope.it. (Source: Bioinformatics)

MOODS: fast search for position weight matrix matches in DNA sequences

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

Summary: MOODS (MOtif Occurrence Detection Suite) is a software package for matching position weight matrices against DNA sequences. MOODS implements state-of-the-art online matching algorithms, achieving considerably faster scanning speed than with a simple brute-force search. MOODS is written in C++, with bindings for the popular BioPerl and Biopython toolkits. It can easily be adapted for different purposes and integrated into existing workflows. It can also be used as a C++ library. Availability: The package with documentation and examples of usage is available at http://www.cs.helsinki.fi/group/pssmfind. The source code is also available under the terms of a GNU General Public License (GPL). Contact: janne.h.korhonen@helsinki.fi (Source: Bioinformatics)

Automatically classifying sentences in full-text biomedical articles into Introduction, Methods, Results and Discussion

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

Discussion (IMRAD). Classifying sentences into these categories can benefit many other text-mining tasks. Although many studies have applied different approaches for automatically classifying sentences in MEDLINE abstracts into the IMRAD categories, few have explored the classification of sentences that appear in full-text biomedical articles. We first evaluated whether sentences in full-text biomedical articles could be reliably annotated into the IMRAD format and then explored different approaches for automatically classifying these sentences into the IMRAD categories. Our results show an overall annotation agreement of 82.14% with a Kappa score of 0.756. The best classification system is a multinomial naïve Bayes classifier trained on manually annotated data that achieved 91.95% ac...

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Functionally guided alignment of protein interaction networks for module detection

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

Motivation: Functional module detection within protein interaction networks is a challenging problem due to the sparsity of data and presence of errors. Computational techniques for this task range from purely graph theoretical approaches involving single networks to alignment of multiple networks from several species. Current network alignment methods all rely on protein sequence similarity to map proteins across species. Results: Here we carry out network alignment using a protein functional similarity measure. We show that using functional similarity to map proteins across species improves network alignment in terms of functional coherence and overlap with experimentally verified protein complexes. Moreover, the results from functional similarity-based network alignment display little o...

Computing the shortest elementary flux modes in genome-scale metabolic networks

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

Motivation: Elementary flux modes (EFMs) represent a key concept to analyze metabolic networks from a pathway-oriented perspective. In spite of considerable work in this field, the computation of the full set of elementary flux modes in large-scale metabolic networks still constitutes a challenging issue due to its underlying combinatorial complexity. Results: In this article, we illustrate that the full set of EFMs can be enumerated in increasing order of number of reactions via integer linear programming. In this light, we present a novel procedure to efficiently determine the K-shortest EFMs in large-scale metabolic networks. Our method was applied to find the K-shortest EFMs that produce lysine in the genome-scale metabolic networks of Escherichia coli and Corynebacterium glutamicum. A...

Combining tissue transcriptomics and urine metabolomics for breast cancer biomarker identification

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

In this study, a systematic method is proposed for identifying metabolic biomarkers in urine samples by selecting candidate biomarkers from altered genome-wide gene expression signatures of cancer cells. Biomarkers identified by the present study have increased coherence and robustness because the significances of biomarkers are validated in both gene expression profiles and metabolic profiles. Results: The proposed method was applied to the gene expression profiles and urine samples of 50 breast cancer patients and 50 normal persons. Nine altered metabolic pathways were identified from the breast cancer gene expression signatures. Among these altered metabolic pathways, four metabolic biomarkers (Homovanillate, 4-hydroxyphenylacetate, 5-hydroxyindoleacetate and urea) were identified to be...

How and when should interactome-derived clusters be used to predict functional modules and protein function?

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

Motivation: Clustering of protein–protein interaction networks is one of the most common approaches for predicting functional modules, protein complexes and protein functions. But, how well does clustering perform at these tasks? Results: We develop a general framework to assess how well computationally derived clusters in physical interactomes overlap functional modules derived via the Gene Ontology (GO). Using this framework, we evaluate six diverse network clustering algorithms using Saccharomyces cerevisiae and show that (i) the performances of these algorithms can differ substantially when run on the same network and (ii) their relative performances change depending upon the topological characteristics of the network under consideration. For the specific task of function predict...

Automatic assignment of reaction operators to enzymatic reactions

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

Conclusion: The analysis and comparison of enzymatic reactions according to their electron shift patterns is defining enzyme groups characterised by unique reaction cores. Our results demonstrate the applicability of the Dugundji–Ugi model as a reasonable pre-classification system allowing an objective and rational view on biochemical reactions. Availability: The program to generate reaction matrix descriptors is available upon request. Contact: d.schomburg@tu-bs.de (Source: Bioinformatics)

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Qupe--a Rich Internet Application to take a step forward in the analysis of mass spectrometry-based quantitative proteomics experiments

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

Motivation: The goal of present -omics sciences is to understand biological systems as a whole in terms of interactions of the individual cellular components. One of the main building blocks in this field of study is proteomics where tandem mass spectrometry (LC-MS/MS) in combination with isotopic labelling techniques provides a common way to obtain a direct insight into regulation at the protein level. Methods to identify and quantify the peptides contained in a sample are well established, and their output usually results in lists of identified proteins and calculated relative abundance values. The next step is to move ahead from these abstract lists and apply statistical inference methods to compare measurements, to identify genes that are significantly up- or down-regulated, or to dete...

Integration of heterogeneous expression data sets extends the role of the retinol pathway in diabetes and insulin resistance

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

Motivation: Type 2 diabetes is a chronic metabolic disease that involves both environmental and genetic factors. To understand the genetics of type 2 diabetes and insulin resistance, the DIabetes Genome Anatomy Project (DGAP) was launched to profile gene expression in a variety of related animal models and human subjects. We asked whether these heterogeneous models can be integrated to provide consistent and robust biological insights into the biology of insulin resistance. Results: We perform integrative analysis of the 16 DGAP data sets that span multiple tissues, conditions, array types, laboratories, species, genetic backgrounds and study designs. For each data set, we identify differentially expressed genes compared with control. Then, for the combined data, we rank genes according to...

Bayesian detection of non-sinusoidal periodic patterns in circadian expression data

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

We present an analysis of variance (ANOVA) periodicity detector and its Bayesian extension that can be used to discover periodic transcripts of arbitrary shapes from replicated gene expression profiles. The models are applicable when the profiles are collected at comparable time points for at least two cycles. We provide an empirical Bayes procedure for estimating parameters of the prior distributions and derive closed-form expressions for the posterior probability of periodicity, enabling efficient computation. The model is applied to two datasets profiling circadian regulation in murine liver and skeletal muscle, revealing a substantial number of previously undetected non-sinusoidal periodic transcripts in each. We also apply quantitative real-time PCR to several highly ranked non-sinuso...

The interwinding nature of protein-protein interfaces and its implication for protein complex formation

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

Motivation: Structural features at protein–protein interfaces can be studied to understand protein–protein interactions. It was noticed that in a dataset of 45 multimeric proteins the interface could either be described as flat against flat or protruding/interwound. In the latter, residues within one chain were surrounded by those in other chains, whereas in the former they were not. Results: A simple method was developed that could distinguish between these two types with results that matched those made by a human annotator. Applying this automatic method to a large dataset of 888 structures, chains at interfaces were categorized as non-surrounded or surrounded. It was found that the surrounded set had a significantly lower folding tendency using a sequence based measure, than...

LIBRUS: combined machine learning and homology information for sequence-based ligand-binding residue prediction

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

Motivation: Identifying residues that interact with ligands is useful as a first step to understanding protein function and as an aid to designing small molecules that target the protein for interaction. Several studies have shown that sequence features are very informative for this type of prediction, while structure features have also been useful when structure is available. We develop a sequence-based method, called LIBRUS, that combines homology-based transfer and direct prediction using machine learning and compare it to previous sequence-based work and current structure-based methods. Results: Our analysis shows that homology-based transfer is slightly more discriminating than a support vector machine learner using profiles and predicted secondary structure. We combine these two appr...

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Reproducing the manual annotation of multiple sequence alignments using a SVM classifier

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

We present here an automated editing method based on the classification of ‘valid’ and ‘invalid’ sites. Results: A support vector machine (SVM) classifier is trained to reproduce the decisions made during manual editing with an accuracy of 95.0%. This implies that manual editing can be made reproducible and applied to large-scale analyses. We further demonstrate that it is possible to retrain/extend the training of the classifier by providing examples of multiple sequence alignment (MSA) annotation. Near optimal training can be achieved with only 1000 annotated sites, or roughly three samples of protein sequence alignments. Availability: This method is implemented in the software MANUEL, licensed under the GPL. A web-based application for single and batch job is ava...

Adaptive multi-agent architecture for functional sequence motifs recognition

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

Motivation: Accurate genome annotation or protein function prediction requires precise recognition of functional sequence motifs. Many computational motif prediction models have been proposed. Due to the complexity of the biological data, it may be desirable to apply an integrated approach that uses multiple models for analysis. Results: In this article, we propose a novel multi-agent architecture for the general purpose of functional sequence motif recognition. The approach takes advantage of the synergy provided by multiple agents through the employment of different agents equipped with distinctive problem solving skills and promotes the collaborations among them through decision maker (DM) agents that work as classifier ensembles. A genetic algorithm-based fusion strategy is applied whi...

Detection of new protein domains using co-occurrence: application to Plasmodium falciparum

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

Motivation: Hidden Markov models (HMMs) have proved to be a powerful tool for protein domain identification in newly sequenced organisms. However, numerous domains may be missed in highly divergent proteins. This is the case for Plasmodium falciparum proteins, the main causal agent of human malaria. Results: We propose a method to improve the sensitivity of HMM domain detection by exploiting the tendency of the domains to appear preferentially with a few other favorite domains in a protein. When sequence information alone is not sufficient to warrant the presence of a particular domain, our method enables its detection on the basis of the presence of other Pfam or InterPro domains. Moreover, a shuffling procedure allows us to estimate the false discovery rate associated with the results. A...

HHsvm: fast and accurate classification of profile-profile matches identified by HHsearch

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

Motivation: Recently developed profile–profile methods rival structural comparisons in their ability to detect homology between distantly related proteins. Despite this tremendous progress, many genuine relationships between protein families cannot be recognized as comparisons of their profiles result in scores that are statistically insignificant. Results: Using known evolutionary relationships among protein superfamilies in SCOP database, support vector machines were trained on four sets of discriminatory features derived from the output of HHsearch. Upon validation, it was shown that the automatic classification of all profile–profile matches was superior to fixed threshold-based annotation in terms of sensitivity and specificity. The effectiveness of this approach was demon...

Genome analysis with inter-nucleotide distances

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

The objective of this work was to find a mapping scheme directly related to DNA characteristics and that would be useful in discriminating between different species. Mathematical models to explore DNA correlation structures may contribute to a better knowledge of the DNA and to find a concise DNA description. Results: We developed a methodology to process DNA sequences based on inter-nucleotide distances. Our main contribution is a method to obtain genomic signatures for complete genomes, based on the inter-nucleotide distances, that are able to discriminate between different species. Using these signatures and hierarchical clustering, it is possible to build phylogenetic trees. Phylogenetic trees lead to genome differentiation and allow the inference of phylogenetic relations. The phyloge...

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Quantitative measurement of aging using image texture entropy

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

Motivation: A key element in understanding the aging of Caenorhabditis elegans is objective quantification of the morphological differences between younger and older animals. Here we propose to use the image texture entropy as an objective measurement that reflects the structural deterioration of the C.elegans muscle tissues during aging. Results: The texture entropy and directionality of the muscle microscopy images were measured using 50 animals on Days 0, 2, 4, 6, 8, 10 and 12 of adulthood. Results show that the entropy of the C.elegans pharynx tissues increases as the animal ages, but a sharper increase was measured between Days 2 and 4, and between Days 8 and 10. These results are in agreement with gene expression findings, and support the contention that the process of C.elegans agin...

Identifiability of isoform deconvolution from junction arrays and RNA-Seq

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

Motivation: Splice junction microarrays and RNA-seq are two popular ways of quantifying splice variants within a cell. Unfortunately, isoform expressions cannot always be determined from the expressions of individual exons and splice junctions. While this issue has been noted before, the extent of the problem on various platforms has not yet been explored, nor have potential remedies been presented. Results: We propose criteria that will guarantee identifiability of an isoform deconvolution model on exon and splice junction arrays and in RNA-Seq. We show that up to 97% of 2256 alternatively spliced human genes selected from the RefSeq database lead to identifiable gene models in RNA-seq, with similar results in mouse. However, in the Human Exon array only 26% of these genes lead to identif...

Lost in translation: an assessment and perspective for computational microRNA target identification

Bioinformatics — Tue, 17 Nov 2009 15:51:19 +0100

MicroRNAs (miRNAs) are a class of short endogenously expressed RNA molecules that regulate gene expression by binding directly to the messenger RNA of protein coding genes. They have been found to confer a novel layer of genetic regulation in a wide range of biological processes. Computational miRNA target prediction remains one of the key means used to decipher the role of miRNAs in development and disease. Here we introduce the basic idea behind the experimental identification of miRNA targets and present some of the most widely used computational miRNA target identification programs. The review includes an assessment of the prediction quality of these programs and their combinations. Contact: p.alexiou@fleming.gr Supplementary information: Supplementary data are available at Bioinformat...

Interactive surface-guided segmentation of brain MRI data

Computers in Biology and Medicine — Mon, 16 Nov 2009 16:28:45 +0100

Abstract: MRI segmentation is a process of deriving semantic information from volume data. For brain MRI data, segmentation is initially performed at a voxel level and then continued at a brain surface level by generating its approximation. While successful most of the time, automated brain segmentation may leave errors which have to be removed interactively by editing individual 2D slices. We propose an approach for correcting these segmentation errors in 3D modeling space. We actively use the brain surface, which is estimated (potentially wrongly) in the automated FreeSurfer segmentation pipeline. It allows us to work with the whole data set at once, utilizing the context information and correcting several slices simultaneously. Proposed heuristic editing support and automatic visual hig...

Adaptive threshold method for the peak detection of photoplethysmographic waveform

Computers in Biology and Medicine — Mon, 16 Nov 2009 16:28:45 +0100

Abstract: Photoplethysmography (PPG)-based temporal analyses have been widely used as a useful analytical method in physiological and cardiovascular diagnosis. Most of temporal approaches of PPG are based on detected peak points, peak and foot of PPG. The aim of presented study is the development of improved peak detection algorithm of PPG waveform. The present study demonstrates a promising approach to overcome respiration effect and to detect PPG peak. More extensive investigation is necessary to adapt for the cardiovascular diseases, whose PPG morphology has different form. (Source: Computers in Biology and Medicine)

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Pleural nodule identification in low-dose and thin-slice lung computed tomography

Computers in Biology and Medicine — Mon, 16 Nov 2009 16:28:45 +0100

Abstract: A completely automated system for the identification of pleural nodules in low-dose and thin-slice computed tomography (CT) of the lung has been developed. The directional-gradient concentration method has been applied to the pleura surface and combined with a morphological opening-based procedure to generate a list of nodule candidates. Each nodule candidate is characterized by 12 morphological and textural features, which are analyzed by a rule-based filter and a neural classifier. This detection system has been developed and validated on a dataset of 42 annotated CT scans. The k-fold cross validation has been used to evaluate the neural classifier performance. The system performance variability due to different ground truth agreement levels is discussed. In particular, the poo...

Computer method for perinatal screening of cardiac murmur using fetal phonocardiography

Computers in Biology and Medicine — Mon, 16 Nov 2009 16:28:45 +0100

Abstract: The main purpose of this paper is to demonstrate the capability of fetal phonocardiographic measurements to indicate some congenital heart defects. It deals with the results of investigations carried out during the last four years involving 820 pregnant women. During the investigations fetal cardiac murmurs presenting typical waveforms and incidences of acoustic signals were recorded. Causes of these murmurs are suggested based on comparison with the well-known waveforms of infants and children. A sophisticated signal processing method for murmur discovery is presented, that is also useful for automatic perinatal screening after the 28th week of gestation. By these means low-risk population may also be fully tested for cardiac malfunctions. (Source: Computers in Biology and Medic...

A computationally advantageous system for fitting probabilistic decompression models to empirical data

Computers in Biology and Medicine — Mon, 16 Nov 2009 16:28:45 +0100

Abstract: To investigate the nature and mechanisms of decompression sickness (DCS), we developed a system for evaluating the success of decompression models in predicting DCS probability from empirical data. Model parameters were estimated using maximum likelihood techniques. Exact integrals of risk functions and tissue kinetics transition times were derived. Agreement with previously published results was excellent including: (a) maximum likelihood values within one log-likelihood unit of previous results and improvements by re-optimization; (b) mean predicted DCS incidents within 1.4% of observed DCS; and (c) time of DCS occurrence prediction. Alternative optimization and homogeneous parallel processing techniques yielded faster model optimization times. (Source: Computers in Biology and...

An interactive graphical user interface for comprehensive analysis of human and swine cardiac monophasic action potential

Computers in Biology and Medicine — Mon, 16 Nov 2009 16:28:44 +0100

Abstract: This research describes a novel monophasic action potential (MAP) annotation algorithm coupled with an interactive graphical user interface (GUI). This algorithm incorporates a number of features to reduce error. Additionally, the GUI has several convenient features to view and manipulate the annotation visually. We analyzed data from swine and human hearts in normal sinus rhythm, during myocardial ischemia, and while eliciting high rates. Validation results indicate correlation >90% between human and computer measurements. This analysis system has several clinical applications in electrophysiological interventions, pharmacodynamic therapies, ischemia detection, and/or in assessment of the time course of electrical activation. (Source: Computers in Biology and Medicine)

Automated classification of cells in sub-epithelial connective tissue of oral sub-mucous fibrosis—An SVM based approach

Computers in Biology and Medicine — Mon, 16 Nov 2009 16:28:44 +0100

In this study segmentation and classification of sub-epithelial connective tissue (SECT) cells except endothelial cells in oral mucosa of normal and OSF conditions has been reported. Segmentation has been carried out using multi-level thresholding and subsequently the cell population has been classified using support vector machine (SVM) based classifier. Moreover, the geometric features used here have been observed to be statistically significant, which enhance the statistical learning potential and classification accuracy of the classifier. Automated classification of SECT cells characterizes this precancerous condition very precisely in a quantitative manner and unveils the opportunity to understand OSF related changes in cell population having definite geometric properties. The paper p...

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A combinatorial feature selection approach to describe the QSAR of dual site inhibitors of acetylcholinesterase

Computers in Biology and Medicine — Mon, 16 Nov 2009 16:28:44 +0100

Abstract: Regarding the great potential of dual binding site inhibitors of acetylcholinesterase as the future potent drugs of Alzheimer's disease, this study was devoted to extraction of the most effective structural features of these inhibitors from among a large number of quantitative descriptors. To do this, we adopted a unique approach in quantitative structure–activity relationships. An efficient feature selection method was emphasized in such an approach, using the confirmative results of different routine and novel feature selection methods. The proposed methods generated quite consistent results ensuring the effectiveness of the selected structural features. (Source: Computers in Biology and Medicine)

An EMG-driven model to estimate muscle forces and joint moments in stroke patients

Computers in Biology and Medicine — Mon, 16 Nov 2009 16:28:44 +0100

Abstract: Individuals following stroke exhibit altered muscle activation and movement patterns. Improving the efficiency of gait can be facilitated by knowing which muscles are affected and how they contribute to the pathological pattern. In this paper we present an electromyographically (EMG) driven musculoskeletal model to estimate muscle forces and joint moments. Subject specific EMG for the primary ankle plantar and dorsiflexor muscles, and joint kinematics during walking for four subjects following stroke were used as inputs to the model to predict ankle joint moments during stance. The model's ability to predict the joint moment was evaluated by comparing the model output with the moment computed using inverse dynamics. The model did predict the ankle moment with acceptable accuracy,...

On the discrimination of patho-physiological states in epilepsy by means of dynamical measures

Computers in Biology and Medicine — Mon, 16 Nov 2009 16:28:44 +0100

Abstract: In the present paper a number of techniques were applied to determine the effects of epileptic seizure on spontaneous ongoing EEG. The idea is that seizure represents transitions of an epileptic brain from its normal (chaotic) state to an abnormal (more ordered) state. Some nonlinear measures including correlation dimension, maximum Lyapunov exponent and wavelet entropy and a graphical tool, named recurrence plot, as well as a novel technique that collects some statistics of the state space organization were used to characterize interictal, preictal and ictal states and derivate a phase transition. The novelty of this work includes of introducing new types of indicators base upon some nonlinear features besides of proposing a new feature of point distribution in phase space. Our ...

Classification of breast tissues using Moran's index and Geary's coefficient as texture signatures and SVM

Computers in Biology and Medicine — Mon, 16 Nov 2009 16:28:44 +0100

Abstract: Female breast cancer is the major cause of cancer-related deaths in western countries. Efforts in computer vision have been made in order to help improving the diagnostic accuracy by radiologists. In this paper, we present a methodology that uses Moran's index and Geary's coefficient measures in breast tissues extracted from mammogram images. These measures are used as input features for a support vector machine classifier with the purpose of distinguishing tissues between normal and abnormal cases as well as classifying them into benign and malignant cancerous cases. The use of both proposed techniques showed to be very promising, since we obtained an accuracy of 96.04% and Az ROC of 0.946 with Geary's coefficient and an accuracy of 99.39% and Az ROC of 1 with Moran's index to d...

Editorial Board & Publication information

Computers in Biology and Medicine — Mon, 16 Nov 2009 16:28:43 +0100

(Source: Computers in Biology and Medicine)

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Algorithms for effective querying of compound graph-based pathway databases

BMC Bioinformatics - Latest articles — Mon, 16 Nov 2009 00:00:00 +0100

Conclusions: The PATIKA Project Web site is http://www.patika.org.PATIKAweb version 2.1 is available at http://web.patika.org. (Source: BMC Bioinformatics - Latest articles)

Assessing the Quality of Whole Genome Alignments in Bacteria

Advances in Bioinformatics — Sun, 15 Nov 2009 15:56:35 +0100

Comparing genomes is an essential preliminary step to solve many problems in biology. Matching long similar segments between two genomes is a precondition for their evolutionary, genetic, and genome rearrangement analyses. Though various comparison methods have been developed in recent years, a quantitative assessment of their performance is lacking. Here, we describe two families of assessment measures whose purpose is to evaluate bacteria-oriented comparison tools. The first measure is based on how well the genome segmentation fits the gene annotation of the studied organisms; the second uses the number of segments created by the segmentation and the percentage of the two genomes that are conserved. The effectiveness of the two measures is demonstrated by applying them to the results of ...

Response of Tumor Spheroids to Radiation: Modeling and Parameter Estimation.

Bulletin of Mathematical Biology — Sat, 14 Nov 2009 00:00:00 +0100

Authors: Bertuzzi A, Bruni C, Fasano A, Gandolfi A, Papa F, Sinisgalli C We propose a spatially distributed continuous model for the spheroid response to radiation, in which the oxygen distribution is represented by means of a diffusion-consumption equation and the radiosensitivity parameters depend on the oxygen concentration. The induction of lethally damaged cells by a pulse of radiation, their death, and the degradation of dead cells are included. The compartments of lethally damaged cells and of dead cells are subdivided into different subcompartments to simulate the delays that occur in cell death and cell degradation, with a gain in model flexibility. It is shown that, for a single irradiation and under the hypothesis of a sufficiently small spheroid radius, the model can be ref...

Hyperbolic Saturation.

Bulletin of Mathematical Biology — Sat, 14 Nov 2009 00:00:00 +0100

Authors: Jackson JH, Maccluer CR Several hyperbolically saturating empirical models, such as the Michaelis-Menten rate equation, Monod's relative population growth rate, competitive inhibition, and Langmuir's adsorption, are rederived from a simple queuing relation. The resulting derivations reveal and potentially explain the underlying structure and meaning of such empirical models. This view is proposed as a unifying heuristic. PMID: 19915923 [PubMed - as supplied by publisher] (Source: Bulletin of Mathematical Biology)

Efficient or Inaccurate? Analytical and Numerical Modelling of Random Search Strategies.

Bulletin of Mathematical Biology — Sat, 14 Nov 2009 00:00:00 +0100

Authors: James A, Pitchford JW, Plank MJ A large number of observational and theoretical studies have investigated animal movement strategies for finding randomly located food items. Many of these studies have claimed that a particular strategy is advantageous over other strategies or that the spatial distribution of the food items affects the search efficiency. Here, we study a deliberately idealised problem, in which a blind forager searches for re-visitable food items. We show analytically that the forager's efficiency is completely independent of both its movement strategy and the spatial pattern of the food items and depends only on the density of food in the environment. However, in some cases, apparent optima in search strategies can arise as artefacts of inappropriate and inacc...

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On the Modelling of Biological Patterns with Mechanochemical Models: Insights from Analysis and Computation.

Bulletin of Mathematical Biology — Sat, 14 Nov 2009 00:00:00 +0100

Authors: Moreo P, Gaffney EA, García-Aznar JM, Doblaré M The diversity of biological form is generated by a relatively small number of underlying mechanisms. Consequently, mathematical and computational modelling can, and does, provide insight into how cellular level interactions ultimately give rise to higher level structure. Given cells respond to mechanical stimuli, it is therefore important to consider the effects of these responses within biological self-organisation models. Here, we consider the self-organisation properties of a mechanochemical model previously developed by three of the authors in Acta Biomater. 4, 613-621 (2008), which is capable of reproducing the behaviour of a population of cells cultured on an elastic substrate in response to a variety of stimuli. ...

Maximum Urine Concentrating Capability in a Mathematical Model of the Inner Medulla of the Rat Kidney.

Bulletin of Mathematical Biology — Sat, 14 Nov 2009 00:00:00 +0100

Authors: Marcano M, Layton AT, Layton HE In a mathematical model of the urine concentrating mechanism of the inner medulla of the rat kidney, a nonlinear optimization technique was used to estimate parameter sets that maximize the urine-to-plasma osmolality ratio (U/P) while maintaining the urine flow rate within a plausible physiologic range. The model, which used a central core formulation, represented loops of Henle turning at all levels of the inner medulla and a composite collecting duct (CD). The parameters varied were: water flow and urea concentration in tubular fluid entering the descending thin limbs and the composite CD at the outer-inner medullary boundary; scaling factors for the number of loops of Henle and CDs as a function of medullary depth; location and increase rate ...

Merging Mixture Components for Cell Population Identification in Flow Cytometry

Advances in Bioinformatics — Thu, 12 Nov 2009 16:20:24 +0100

We present a framework for the identification of cell subpopulations in flow cytometry data based on merging mixture components using the flowClust methodology. We show that the cluster merging algorithm under our framework improves model fit and provides a better estimate of the number of distinct cell subpopulations than either Gaussian mixture models or flowClust, especially for complicated flow cytometry data distributions. Our framework allows the automated selection of the number of distinct cell subpopulations and we are able to identify cases where the algorithm fails, thus making it suitable for application in a high throughput FCM analysis pipeline. Furthermore, we demonstrate a method for summarizing complex merged cell subpopulations in a simple manner that integrat...

iFlow: A Graphical User Interface for Flow Cytometry Tools in Bioconductor

Advances in Bioinformatics — Thu, 12 Nov 2009 16:20:24 +0100

Flow cytometry (FCM) has become an important analysis technology in health care and medical research, but the large volume of data produced by modern high-throughput experiments has presented significant new challenges for computational analysis tools. The development of an FCM software suite in Bioconductor represents one approach to overcome these challenges. In the spirit of the R programming language (Tree Star Inc., “FlowJo”), these tools are predominantly console-driven, allowing for programmatic access and rapid development of novel algorithms. Using this software requires a solid understanding of programming concepts and of the R language. However, some of these tools|in particular the statistical graphics and novel analytical methods|are also useful for nonprogrammers....

Interaction of Tumor with Its Micro-environment: A Mathematical Model.

Bulletin of Mathematical Biology — Thu, 12 Nov 2009 00:00:00 +0100

Authors: Kim Y, Friedman A This paper is concerned with early development of transformed epithelial cells (TECs) in the presence of fibroblasts in the tumor micro-environment. These two types of cells interact by means of cytokines such as transforming growth factor (TGF-beta) and epidermal growth factor (EGF) secreted, respectively, by the TECs and the fibroblasts. As this interaction proceeds, TGF-beta induces fibroblasts to differentiate into myofibroblasts which secrete EGF at a larger rate than fibroblasts. We monitor the entire process in silico, in a setup which mimics experiments in a Tumor Chamber Invasion Assay, where a semi-permeable membrane coated by extracellular matrix (ECM) is placed between two chambers, one containing TECs and another containing fibroblasts. We develo...

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Mathematical Model for Optimal Use of Sulfadoxine-Pyrimethamine as a Temporary Malaria Vaccine.

Bulletin of Mathematical Biology — Thu, 12 Nov 2009 00:00:00 +0100

Authors: Dembele B, Friedman A, Yakubu AA In this paper, we introduce a deterministic malaria model for determining the drug administration protocol that leads to the smallest first malaria episodes during the wet season. To explore the effects of administering the malaria drug on different days during the wet season while minimizing the potential harmful effects of drug overdose, we define 40 drug administration protocols. Our results fit well with the clinical studies of Coulibaly et al. at a site in Mali. In addition, we provide protocols that lead to smaller number of first malaria episodes during the wet season than the protocol of Coulibaly et al. PMID: 19908101 [PubMed - as supplied by publisher] (Source: Bulletin of Mathematical Biology)

Linguistic feature analysis for protein interaction extraction

BMC Bioinformatics - Latest articles — Thu, 12 Nov 2009 00:00:00 +0100

Conclusions: Our findings suggest that grammatical relations play an important role in the interaction extraction task. Moreover, the net advantage of adding lexical and shallow syntactic features is small related to the number of added features. This implies that efficient classifiers can be built by using only a small fraction of the features that are typically being used in recent approaches. (Source: BMC Bioinformatics - Latest articles)

The challenges of informatics in synthetic biology: from biomolecular networks to artificial organisms.

Briefings in Bioinformatics — Wed, 11 Nov 2009 00:00:00 +0100

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...

Functional phosphoproteomic profiling of phosphorylation sites in membrane fractions of salt-stressed Arabidopsis thaliana

Proteome Science — Tue, 10 Nov 2009 00:00:00 +0100

Conclusion: In this study, we successfully identified novel salt stress-responsive protein phosphorylation sites from membrane isolates of abiotic-stressed plants by membrane shaving followed by Zr4+-IMAC enrichment. The identified phosphorylation sites can be important in the salt stress response in plants. (Source: Proteome Science)

An empirical Bayesian approach for model-based inference of cellular signaling networks

BMC Bioinformatics - Latest articles — Mon, 09 Nov 2009 00:00:00 +0100

Conclusions: In summary, an empirical Bayesian approach was developed for inferring the confidence that one can place in a particular model that describes signal transduction mechanisms and for inferring inconsistencies in experimental measurements. (Source: BMC Bioinformatics - Latest articles)

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A Lossless Compression Algorithm for DNA sequences.

International Journal of Bioinformatics Research and Applications — Sat, 07 Nov 2009 07:10:03 +0100

Authors: Soliman TH, Gharib TF, Abo-Alian A, El Sharkawy MA The increase of the amount of DNA sequences requires efficient computational algorithms for performing sequence comparison and analysis. Standard compression algorithms are not able to compress DNA sequences because they do not consider special characteristics of DNA sequences (i.e., DNA sequences contain several approximate repeats and complimentary palindromes). Recently, new algorithms have been proposed to compress DNA sequences, often using detection of long approximate repeats. The current work proposes a Lossless Compression Algorithm (LCA), providing a new encoding method. LCA achieves a better compression ratio than that of existing DNA-oriented compression algorithms, when compared to GenCompress, DNACompress, and DN...

Insilico analysis of homocamptothecin (hCPT) analogues for anti-tumour activity.

International Journal of Bioinformatics Research and Applications — Sat, 07 Nov 2009 07:10:03 +0100

Authors: Vadwai V, Devaraj S Cancer being a leading cause of death, the development of anti-cancer drugs like Camptothecin (CPT) has been promoted. CPT has lactone ring instability and lacks lipophilicity resulting in drug efflux. Owing to these limitations, homocamptothecin (hCPT), a CPT analogue was developed, which due to seven membered beta-hydroxylactone ring has better lipophilicity leading to reduced drug efflux. Analogues of hCPT were designed and docked into catalytic site of 1t8i (PDB id) protein (top-I). The docking energies and formation of hydrogen-bonds between the analogue and protein were compared with the original hCPT. Further, ADME properties, LogP and IC50 values were determined computationally. PMID: 19887335 [PubMed - in process] (Source: International Journal...

Modifications of ampicillin structure and its implication: an in-silico approach.

International Journal of Bioinformatics Research and Applications — Sat, 07 Nov 2009 07:10:03 +0100

Authors: Poddar R, Mathur A, Kawalekar OU, Rai A, Structural modifications of the existing ampicillin are much needed for saving patients from ampicillin-resistant microorganisms. A number of new molecules were generated by side chain modification of the existing ampicillin structure. Armed with molecular docking softwares like FlexiDOC, GLIDE, and AutoDOCK, a docking study was performed. Interaction between new molecules and target protein (1W2N) was also executed. Finally, we arranged new molecules according to docking scores, which directly reflects the binding affinity to the receptor protein. PMID: 19887336 [PubMed - in process] (Source: International Journal of Bioinformatics Research and Applications)

Identifying cell cycle regulators and combinatorial interactions among transcription factors with microarray data and ChIP-chip data.

International Journal of Bioinformatics Research and Applications — Sat, 07 Nov 2009 07:10:03 +0100

Authors: Chen T, Li F In this paper, we integrate transcriptional regulatory modelling with temporal correlation analysis between one Transcription Factor (TF) and its corresponding cell cycle-regulated targets to investigate Cell Cycle Regulators (CCRs) and combinatorial interactions among TFs across the cell cycle in Saccharomyces cerevisiae. Our method is developed based on the rationale that if one TF or one TF combinatorial interaction takes more possibilities of sharing common cell cycle-regulated targets with other TFs, this TF or TF combinatorial interaction is more likely to control the cell cycle. Our results reveal abundant CCRs and TF co-operativities supported by biological experiments or other computational methods. PMID: 19887337 [PubMed - in process] (Source: Intern...

Investigating an Artificial Immune System to strengthen protein structure prediction and protein coding region identification using the Cellular Automata classifier.

International Journal of Bioinformatics Research and Applications — Sat, 07 Nov 2009 07:10:03 +0100

Authors: Sree PK, Babu IR, Devi NS Genes carry the instructions for making proteins that are found in a cell as a specific sequence of nucleotides that are found in DNA molecules. But, the regions of these genes that code for proteins may occupy only a small region of the sequence. Identification of the coding regions plays a vital role in understanding these genes. In this paper we have explored an Artificial Immune System (AIS) that can be used to strengthen and identify the protein coding regions in a genomic DNA system in changing environments and the CA technique for protein structure prediction of small alpha/beta proteins using Rosetta. From an initial round of Rosetta sampling, we learn properties of the energy landscape that guide a subsequent round of sampling toward lower-en...

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SnS-Align: a graphic tool for alignment of distantly related proteins.

International Journal of Bioinformatics Research and Applications — Sat, 07 Nov 2009 07:10:03 +0100

Authors: Manyam G, Baranova A, Skoblov M, Mishra RK Genomic sequences for many animal species are now available in the public domain. Protein similarity search in evolutionarily distant organisms by sequence comparison often turns out to be difficult. Here, we present the Structure and Sequence Alignment (SnS-Align) tool that graphically presents pairwise local alignment of sandwiched protein sequences, a hybrid of the primary protein sequence and its secondary structure. The utility of the tool is demonstrated by sample analysis of the gap junction protein superfamily of innexins/pannexins and the classic myoglobin family. SnS-Align can also be used for demarcation of the structurally conserved domains within superfamilies of paralogous genes. PMID: 19887339 [PubMed - in process] ...

Stability and Bifurcations in an Epidemic Model with Varying Immunity Period.

Bulletin of Mathematical Biology — Sat, 07 Nov 2009 00:00:00 +0100

Authors: Blyuss KB, Kyrychko YN An epidemic model with distributed time delay is derived to describe the dynamics of infectious diseases with varying immunity. It is shown that solutions are always positive, and the model has at most two steady states: disease-free and endemic. It is proved that the disease-free equilibrium is locally and globally asymptotically stable. When an endemic equilibrium exists, it is possible to analytically prove its local and global stability using Lyapunov functionals. Bifurcation analysis is performed using DDE-BIFTOOL and traceDDE to investigate different dynamical regimes in the model using numerical continuation for different values of system parameters and different integral kernels. PMID: 19898905 [PubMed - as supplied by publisher] (Source: Bul...

Irreducibility in RNA Structures.

Bulletin of Mathematical Biology — Thu, 05 Nov 2009 00:00:00 +0100

Authors: Jin EY, Reidys CM In this paper, we study irreducibility in RNA structures. By RNA structure, we mean RNA secondary as well as RNA pseudoknot structures as abstract contact structures. We give an analysis contrasting random and minimum free energy (mfe) configurations and secondary versus pseudoknots structures. In the process, we compute various distributions: the numbers of irreducible substructures and their locations and sizes, parameterized in terms of the maximal number of mutually crossing arcs, k-1, and the minimal size of stacks sigma. In particular, we analyze the size of the largest irreducible substructure for random and mfe structures, which is the key factor for the folding time of mfe configurations. We show that the largest irreducible substructure is typically...

Enrichment and proteomic analysis of plasma membrane from rat dorsal root ganglions

Proteome Science — Thu, 05 Nov 2009 00:00:00 +0100

Conclusion: The aqueous polymer two-phase partition is a simple, rapid and relatively inexpensive method. It is well suitable for the purification of PMs from small amount of tissues. Therefore, it is reasonable for the DRG PM to be enriched by using aqueous two-phase partition as a preferred method. Proteomic analysis showed that DRG PM was rich in proteins involved in the fundamental biological processes including material exchange, energy transformation and information transmission, etc. These data would help to our further understanding of the fundamental DRG functions. (Source: Proteome Science)

RNA folding on the 3D triangular lattice

BMC Bioinformatics - Latest articles — Thu, 05 Nov 2009 00:00:00 +0100

Conclusion: Folding simulation on the 3D triangular lattice is effective method for RNA secondary structure prediction and lattice conformation reconstruction. The visualization software for the lattice conformations of RNA structures is a valuable tool for the study of RNA folding and is a great pedagogic device. (Source: BMC Bioinformatics - Latest articles)

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PrePrint: GPD: A Graph Pattern Diffusion Kernel for Accurate Graph Classification with Applications in Cheminformatics

IEEE/ACM Transactions on Computational Biology and Bioinformatics — Wed, 04 Nov 2009 16:40:37 +0100

Graph data mining is an active research area. Graphs are general modeling tools to organize information from heterogenous sources and have been applied in many scientific, engineering, and business fields. With the fast accumulation of graph data, building highly accurate predictive models for graph data emerges as a new challenge that has not been fully explored in the data mining community. In this paper, we demonstrate a novel technique called graph pattern diffusion kernel (GPD) with applications in cheminformatics. Our idea is to leverage existing frequent pattern discovery methods and to explore the application of kernel classifier (e.g. support vector machine) in building highly accurate graph classification. In our method, we first identify all frequent patterns from a graph databa...

PrePrint: Molecular Function Prediction Using Neighborhood Features

IEEE/ACM Transactions on Computational Biology and Bioinformatics — Wed, 04 Nov 2009 16:40:37 +0100

The recent advent of high throughput methods has generated large amounts of gene interaction data. This has allowed the construction of genome-wide networks. A significant number of genes in such networks remain uncharacterized and predicting the molecular function of these genes remains a major challenge. A number of existing techniques assume that genes with similar functions are topologically close in the network. Our hypothesis is that genes with similar functions observe similar annotation patterns in their neighborhood, regardless of the distance between them in the interaction network. We thus predict molecular functions of uncharacterized genes by comparing their functional neighborhoods to genes of known function. We propose a two-phase approach. First we extract functional neighb...

Rapid detection, classification and accurate alignment of up to a million or more related protein sequences

Bioinformatics — Wed, 04 Nov 2009 13:45:50 +0100

(Source: Bioinformatics)

QuickGO: a web-based tool for Gene Ontology searching

Bioinformatics — Wed, 04 Nov 2009 13:45:50 +0100

Summary: QuickGO is a web-based tool that allows easy browsing of the Gene Ontology (GO) and all associated electronic and manual GO annotations provided by the GO Consortium annotation groups QuickGO has been a popular GO browser for many years, but after a recent redevelopment it is now able to offer a greater range of facilities including bulk downloads of GO annotation data which can be extensively filtered by a range of different parameters and GO slim set generation. Availability and Implementation: QuickGO has implemented in JavaScript, Ajax and HTML, with all major browsers supported. It can be queried online at http://www.ebi.ac.uk/QuickGO. The software for QuickGO is freely available under the Apache 2 licence and can be downloaded from http://www.ebi.ac.uk/QuickGO/installation.h...

Next generation software for functional trend analysis

Bioinformatics — Wed, 04 Nov 2009 13:45:50 +0100

Summary: FuncAssociate is a web application that discovers properties enriched in lists of genes or proteins that emerge from large-scale experimentation. Here we describe an updated application with a new interface and several new features. For example, enrichment analysis can now be performed within multiple gene- and protein-naming systems. This feature avoids potentially serious translation artifacts to which other enrichment analysis strategies are subject. Availability: The FuncAssociate web application is freely available to all users at http://llama.med.harvard.edu/funcassociate. Contact: fritz_roth@hms.harvard.edu (Source: Bioinformatics)

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CMap 1.01: a comparative mapping application for the Internet

Bioinformatics — Wed, 04 Nov 2009 13:45:49 +0100

Summary:CMap is a web-based tool for displaying and comparing maps of any type and from any species. A user can compare an unlimited number of maps, view pair-wise comparisons of known correspondences, and search for maps or for features by name, species, type and accession. CMap is freely available, can run on a variety of database engines and uses only free and open software components. Availability: http://www.gmod.org/cmap Contact: kclark@cshl.edu (Source: Bioinformatics)

Identifying related journals through log analysis

Bioinformatics — Wed, 04 Nov 2009 13:45:49 +0100

Motivation: With the explosion of biomedical literature and the evolution of online and open access, scientists are reading more articles from a wider variety of journals. Thus, the list of core journals relevant to their research may be less obvious and may often change over time. To help researchers quickly identify appropriate journals to read and publish in, we developed a web application for finding related journals based on the analysis of PubMed log data. Availability: http://www.ncbi.nlm.nih.gov/IRET/Journals Contact: luzh@ncbi.nlm.nih.gov Supplementary information: Supplementary data are available at Bioinformatics online. (Source: Bioinformatics)

UniMaP: finding unique mass and peptide signatures in the human proteome

Bioinformatics — Wed, 04 Nov 2009 13:45:49 +0100

We present a publicly available web application that offers information concerning the uniqueness of one or more molecular masses and one or more peptide sequences in the human proteome. When a sequence is found to be unique in humans, the application is able to search across all species querying whether this sequence is unique, not only in humans but also in other species found in the Swiss-Prot Database. The application is also able to search for unique protein fragments derived computationally from enzymatic digestion driven by certain enzymes. Furthermore, the application can list all the unique masses and peptides of a given protein. Through this application, researchers are able to find unique tags, either on a molecular mass level or on a sequence level. These unique tags are remark...

digeR: a graphical user interface R package for analyzing 2D-DIGE data

Bioinformatics — Wed, 04 Nov 2009 13:45:49 +0100

We report on an R package, digeR, with an easy to use graphical user interface for analyzing 2D-DIGE (2D gel) data. It provides a tool for visually looking for potential PTM changes from different biological states and support biomarker discovery through multivariate analysis techniques. Availability: digeR package is freely available from the CRAN: http://cran.r-project.org/web/packages/digeR/index.html. Contact: yue.fan@ucd.ie Supplementary information: Supplementary data are available at Bioinformatics online. (Source: Bioinformatics)

PubMed-EX: a web browser extension to enhance PubMed search with text mining features

Bioinformatics — Wed, 04 Nov 2009 13:45:49 +0100

Summary: PubMed-EX is a browser extension that marks up PubMed search results with additional text-mining information. PubMed-EX's page mark-up, which includes section categorization and gene/disease and relation mark-up, can help researchers to quickly focus on key terms and provide additional information on them. All text processing is performed server-side, freeing up user resources. Availability: PubMed-EX is freely available at http://bws.iis.sinica.edu.tw/PubMed-EX and http://iisr.cse.yzu.edu.tw:8000/PubMed-EX/. Contact: thtsai@saturn.yzu.edu.tw Supplementary information: Supplementary data are available at Bioinformatics online. (Source: Bioinformatics)

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CellClassifier: supervised learning of cellular phenotypes

Bioinformatics — Wed, 04 Nov 2009 13:45:49 +0100

Summary:CellClassifier is a tool for classifying single-cell phenotypes in microscope images. It includes several unique and user-friendly features for classification using multiclass support vector machines Availability: Source code, user manual and SaveObjectSegmentation CellProfiler module available for download at www.cellclassifier.ethz.ch under the GPL license (implemented in Matlab). Contact: pelkmans@imsb.biol.ethz.ch Supplementary information: Supplementary data are available at Bioinformatics online. (Source: Bioinformatics)

Saint: a lightweight integration environment for model annotation

Bioinformatics — Wed, 04 Nov 2009 13:45:49 +0100

Summary: Saint is a web application which provides a lightweight annotation integration environment for quantitative biological models. The system enables modellers to rapidly mark up models with biological information derived from a range of data sources. Availability and Implementation: Saint is freely available for use on the web at http://www.cisban.ac.uk/saint. The web application is implemented in Google Web Toolkit and Tomcat, with all major browsers supported. The Java source code is freely available for download at http://saint-annotate.sourceforge.net. The Saint web server requires an installation of libSBML and has been tested on Linux (32-bit Ubuntu 8.10 and 9.04). Contact: helpdesk@cisban.ac.uk; a.l.lister@ncl.ac.uk Supplementary information: Supplementary data are available a...

Comparative analysis and unification of domain-domain interaction networks

Bioinformatics — Wed, 04 Nov 2009 13:45:49 +0100

Motivation: Certain protein domains are known to preferentially interact with other domains. Several approaches have been proposed to predict domain–domain interactions, and over nine datasets are available. Our aim is to analyse the coverage and quality of the existing resources, as well as the extent of their overlap. With this knowledge, we have the opportunity to merge individual domain interaction networks to construct a comprehensive and reliable database. Results: In this article we introduce a new approach towards comparing domain–domain interaction networks. This approach is used to compare nine predicted domain and protein interaction networks. The networks were used to generate a database of unified domain interactions, UniDomInt. Each interaction in the dataset is s...

A method for visualizing CellML models

Bioinformatics — Wed, 04 Nov 2009 13:45:49 +0100

This article presents a framework that combines a visual language, together with CellML ontologies, to support the visualization of the underlying physical and biological concepts described by the mathematical model and also their relationships with the CellML model. Automated CellML model visualization assists in the interpretation of model concepts and facilitates model communication and exchange between different communities. Contact: sarala.dissanayake@auckland.ac.nz Supplementary information: Supplementary data are available at Bioinformatics online. (Source: Bioinformatics)

Mobyle: a new full web bioinformatics framework

Bioinformatics — Wed, 04 Nov 2009 13:45:49 +0100

Motivation: For the biologist, running bioinformatics analyses involves a time-consuming management of data and tools. Users need support to organize their work, retrieve parameters and reproduce their analyses. They also need to be able to combine their analytic tools using a safe data flow software mechanism. Finally, given that scientific tools can be difficult to install, it is particularly helpful for biologists to be able to use these tools through a web user interface. However, providing a web interface for a set of tools raises the problem that a single web portal cannot offer all the existing and possible services: it is the user, again, who has to cope with data copy among a number of different services. A framework enabling portal administrators to build a network of cooperating...

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Flynet: a genomic resource for Drosophila melanogaster transcriptional regulatory networks

Bioinformatics — Wed, 04 Nov 2009 13:45:49 +0100

Motivation: The highly coordinated expression of thousands of genes in an organism is regulated by the concerted action of transcription factors, chromatin proteins and epigenetic mechanisms. High-throughput experimental data for genome wide in vivo protein–DNA interactions and epigenetic marks are becoming available from large projects, such as the model organism ENCyclopedia Of DNA Elements (modENCODE) and from individual labs. Dissemination and visualization of these datasets in an explorable form is an important challenge. Results: To support research on Drosophila melanogaster transcription regulation and make the genome wide in vivo protein–DNA interactions data available to the scientific community as a whole, we have developed a system called Flynet. Currently, Flynet c...

Characterization of 1H NMR spectroscopic data and the generation of synthetic validation sets

Bioinformatics — Wed, 04 Nov 2009 13:45:49 +0100

Motivation: Common contemporary practice within the nuclear magnetic resonance (NMR) metabolomics community is to evaluate and validate novel algorithms on empirical data or simplified simulated data. Empirical data captures the complex characteristics of experimental data, but the optimal or most correct analysis is unknown a priori; therefore, researchers are forced to rely on indirect performance metrics, which are of limited value. In order to achieve fair and complete analysis of competing techniques more exacting metrics are required. Thus, metabolomics researchers often evaluate their algorithms on simplified simulated data with a known answer. Unfortunately, the conclusions obtained on simulated data are only of value if the data sets are complex enough for results to generalize to...

A dictionary to identify small molecules and drugs in free text

Bioinformatics — Wed, 04 Nov 2009 13:45:49 +0100

Motivation: From the scientific community, a lot of effort has been spent on the correct identification of gene and protein names in text, while less effort has been spent on the correct identification of chemical names. Dictionary-based term identification has the power to recognize the diverse representation of chemical information in the literature and map the chemicals to their database identifiers. Results: We developed a dictionary for the identification of small molecules and drugs in text, combining information from UMLS, MeSH, ChEBI, DrugBank, KEGG, HMDB and ChemIDplus. Rule-based term filtering, manual check of highly frequent terms and disambiguation rules were applied. We tested the combined dictionary and the dictionaries derived from the individual resources on an annotated c...

Metabolite and reaction inference based on enzyme specificities

Bioinformatics — Wed, 04 Nov 2009 13:45:49 +0100

Motivation: Many enzymes are not absolutely specific, or even promiscuous: they can catalyze transformations of more compounds than the traditional ones as listed in, e.g. KEGG. This information is currently only available in databases, such as the BRENDA enzyme activity database. In this article, we propose to model enzyme aspecificity by predicting whether an input compound is likely to be transformed by a certain enzyme. Such a predictor has many applications, for example, to complete reconstructed metabolic networks, to aid in metabolic engineering or to help identify unknown peaks in mass spectra. Results: We have developed a system for metabolite and reaction inference based on enzyme specificities (MaRIboES). It employs structural and stereochemistry similarity measures and molecula...

Improving peptide identification with single-stage mass spectrum peaks

Bioinformatics — Wed, 04 Nov 2009 13:45:49 +0100

Motivation: Database searching is the major peptide identification method in shotgun proteomics. It searches tandem mass spectrometry (MS/MS) spectra against a protein database to identify target peptides. The success of such a database searching method relies on a scoring algorithm that can evaluate the quality of peptide-spectrum matches (PSMs) accurately. However, current scoring algorithms frequently generate inaccurate assignments due to variations and noises in the MS/MS spectra. To address this issue, we like to improve peptide identification by using additional information from other data sources. Results: Single-stage MS data is complementary to MS/MS data in the sense that it provides broader mass coverage but less sequence information. In this article, we show that single-stage ...

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Simultaneous inference of biological networks of multiple species from genome-wide data and evolutionary information: a semi-supervised approach

Bioinformatics — Wed, 04 Nov 2009 13:45:49 +0100

Motivation: The existing supervised methods for biological network inference work on each of the networks individually based only on intra-species information such as gene expression data. We believe that it will be more effective to use genomic data and cross-species evolutionary information from different species simultaneously, rather than to use the genomic data alone. Results: We created a new semi-supervised learning method called Link Propagation for inferring biological networks of multiple species based on genome-wide data and evolutionary information. The new method was applied to simultaneous reconstruction of three metabolic networks of Caenorhabditis elegans, Helicobacter pylori and Saccharomyces cerevisiae, based on gene expression similarities and amino acid sequence similar...

Mining gene functional networks to improve mass-spectrometry-based protein identification

Bioinformatics — Wed, 04 Nov 2009 13:45:49 +0100

Motivation: High-throughput protein identification experiments based on tandem mass spectrometry (MS/MS) often suffer from low sensitivity and low-confidence protein identifications. In a typical shotgun proteomics experiment, it is assumed that all proteins are equally likely to be present. However, there is often other evidence to suggest that a protein is present and confidence in individual protein identification can be updated accordingly. Results: We develop a method that analyzes MS/MS experiments in the larger context of the biological processes active in a cell. Our method, MSNet, improves protein identification in shotgun proteomics experiments by considering information on functional associations from a gene functional network. MSNet substantially increases the number of protein...

Identification of genes involved in the same pathways using a Hidden Markov Model-based approach

Bioinformatics — Wed, 04 Nov 2009 13:45:49 +0100

Motivation: The sequencing of whole genomes from various species has provided us with a wealth of genetic information. To make use of the vast amounts of data available today it is necessary to devise computer-based analysis techniques. Results: We propose a Hidden Markov Model (HMM) based algorithm to detect groups of genes functionally similar to a set of input genes from microarray expression data. A subset of experiments from a microarray is selected based on a set of related input genes. HMMs are trained from the input genes and a group of random gene input sets to provide significance estimates. Every gene in the microarray is scored using all HMMs and significant matches with the input genes are retained. We ran this algorithm on the life cycle of Drosophila microarray data set with...

Learning gene regulatory networks from gene expression measurements using non-parametric molecular kinetics

Bioinformatics — Wed, 04 Nov 2009 13:45:49 +0100

Motivation: Regulation of gene expression is fundamental to the operation of a cell. Revealing the structure and dynamics of a gene regulatory network (GRN) is of great interest and represents a considerably challenging computational problem. The GRN estimation problem is complicated by the fact that the number of gene expression measurements is typically extremely small when compared with the dimension of the biological system. Further, because the gene regulation process is intrinsically complex, commonly used parametric models can provide too simple description of the underlying phenomena and, thus, can be unreliable. In this article, we propose a novel methodology for the inference of GRNs from time-series and steady-state gene expression measurements. The presented framework is based ...

A boosting approach to structure learning of graphs with and without prior knowledge

Bioinformatics — Wed, 04 Nov 2009 13:45:49 +0100

Motivation: Identifying the network structure through which genes and their products interact can help to elucidate normal cell physiology as well as the genetic architecture of pathological phenotypes. Recently, a number of gene network inference tools have appeared based on Gaussian graphical model representations. Following this, we introduce a novel Boosting approach to learn the structure of a high-dimensional Gaussian graphical model motivated by the applications in genomics. A particular emphasis is paid to the inclusion of partial prior knowledge on the structure of the graph. With the increasing availability of pathway information and large-scale gene expression datasets, we believe that conditioning on prior knowledge will be an important aspect in raising the statistical power o...

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Understanding hydrogen-bond patterns in proteins using network motifs

Bioinformatics — Wed, 04 Nov 2009 13:45:49 +0100

Summary: Protein structures can be viewed as networks of contacts (edges) between amino-acid residues (nodes). Here we dissect proteins into sub-graphs consisting of six nodes and their corresponding edges, with an edge being either a backbone hydrogen bond (H-bond) or a covalent interaction. Six thousand three hundred and twenty-two such sub-graphs were found in a large non-redundant dataset of high-resolution structures, from which 35 occur much more frequently than in a random model. Many of these significant sub-graphs (also called network motifs) correspond to sub-structures of helices and β-sheets, as expected. However, others correspond to more exotic sub-structures such as 310 helix, Schellman motif and motifs that were not defined previously. This topological characterization...

Predicting homologous signaling pathways using machine learning

Bioinformatics — Wed, 04 Nov 2009 13:45:49 +0100

We present an automatic approach, Predict Signaling Pathway (PSP), which uses the signaling pathways in well-studied species to predict the roles of proteins in less-studied species. We use a machine learning approach to create a predictor that achieves a generalization F-measure of 78.2% when applied to 11 different pathways across 14 different species. We also show our approach is very effective in predicting the pathways that have not yet been experimentally studied completely. Availability: The list of predicted proteins for all pathways over all considered species is available at http://www.cs.ualberta.ca/~bioinfo/signaling. Contact: bioinfo@cs.ualberta.ca; duane@cs.ualberta.ca (Source: Bioinformatics)

Integrative clustering of multiple genomic data types using a joint latent variable model with application to breast and lung cancer subtype analysis

Bioinformatics — Wed, 04 Nov 2009 13:45:49 +0100

Motivation: The molecular complexity of a tumor manifests itself at the genomic, epigenomic, transcriptomic and proteomic levels. Genomic profiling at these multiple levels should allow an integrated characterization of tumor etiology. However, there is a shortage of effective statistical and bioinformatic tools for truly integrative data analysis. The standard approach to integrative clustering is separate clustering followed by manual integration. A more statistically powerful approach would incorporate all data types simultaneously and generate a single integrated cluster assignment. Methods: We developed a joint latent variable model for integrative clustering. We call the resulting methodology iCluster. iCluster incorporates flexible modeling of the associations between different data...

De novo computational prediction of non-coding RNA genes in prokaryotic genomes

Bioinformatics — Wed, 04 Nov 2009 13:45:49 +0100

We present a novel de novo prediction algorithm for ncRNA genes using features derived from the sequences and structures of known ncRNA genes in comparison to decoys. Using these features, we have trained a neural network-based classifier and have applied it to Escherichia coli and Sulfolobus solfataricus for genome-wide prediction of ncRNAs. Our method has an average prediction sensitivity and specificity of 68% and 70%, respectively, for identifying windows with potential for ncRNA genes in E.coli. By combining windows of different sizes and using positional filtering strategies, we predicted 601 candidate ncRNAs and recovered 41% of known ncRNAs in E.coli. We experimentally investigated six novel candidates using Northern blot analysis and found expression of three candidates: one repre...

Phenotypic categorization of genetic skin diseases reveals new relations between phenotypes, genes and pathways

Bioinformatics — Wed, 04 Nov 2009 13:45:49 +0100

Motivation: Systematic analysis of connection between proteins, their cellular function and phenotypic manifestations in disease is a central problem of biological and clinical research. The solution to this problem requires the development of new approaches to link the rapidly growing dataset of gene–disease associations with the many complex and overlapping phenotypes of human disease. Results: We analyze genetic skin disorders and suggest a manually designed set of elementary phenotypes whose combinations define diseases as points in a multidimensional space, providing a basis for phenotypic disease clustering. Placing the known gene–disease associations in the context of this space reveals new patterns that suggest previously unknown functional links between proteins, signa...

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Proteins related to lipoprotein profile were identified using a pharmaco-proteomic approach as markers for growth response to growth hormone (GH) treatment in short prepubertal children

Proteome Science — Mon, 02 Nov 2009 00:00:00 +0100

Conclusion: Using a proteomic approach we identified biomarkers related to the lipoprotein profile that could be used to predict growth response to GH treatment in prepubertal children who are short as a result of GH-deficiency or who have ISS.These results support our previous findings that apolipoproteins and transthyretin may have a role in GH sensitivity. (Source: Proteome Science)

PrePrint: Microarray Time Course Experiments: Finding Profiles

IEEE/ACM Transactions on Computational Biology and Bioinformatics — Sun, 01 Nov 2009 16:04:18 +0100

We present, in replicate experiments, an alternative approach to select and cluster genes according to a new measure for association between genes. First the procedure normalizes and standardizes the expression profile of each gene and then identifies scaling parameters that will further minimize the distance between replicates of the same gene. Then, the procedure filters out genes with a flat profile, detects differences between replicates and separates genes without significant differences from the rest. For this last group of genes, we define a mean profile for each gene and use it to compute the distance between two genes. Next, a hierarchical clustering procedure is proposed, a statistic is computed for each cluster to determine its compactness and the total number of classes is dete...

Subject Index

Artificial Intelligence in Medicine — Sun, 01 Nov 2009 00:00:00 +0100

(Source: Artificial Intelligence in Medicine)

Author Index

Artificial Intelligence in Medicine — Sun, 01 Nov 2009 00:00:00 +0100

(Source: Artificial Intelligence in Medicine)

An electromechanical based deformable model for soft tissue simulation

Artificial Intelligence in Medicine — Sun, 01 Nov 2009 00:00:00 +0100

Conclusions: The proposed methodology does not only predict the typical behaviours of living tissues, but it also accepts both local and large-range deformations. It also accommodates isotropic, anisotropic and inhomogeneous deformations by simple modification of diffusion coefficients. (Source: Artificial Intelligence in Medicine)

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Entropy and complexity measures for EEG signal classification of schizophrenic and control participants

Artificial Intelligence in Medicine — Sun, 01 Nov 2009 00:00:00 +0100

Conclusion: This study shows that EEG signals can be a useful tool for discrimination of the schizophrenic and control participants. It is suggested that this analysis can be a complementary tool to help psychiatrists diagnosing schizophrenic patients. (Source: Artificial Intelligence in Medicine)

Adapted variable precision rough set approach for EEG analysis

Artificial Intelligence in Medicine — Sun, 01 Nov 2009 00:00:00 +0100

Conclusion: The presented approach is a useful method for substantial attribute reduction in noisy and inconsistent data sets. (Source: Artificial Intelligence in Medicine)

Addressing the flaws of current critical alarms: a fuzzy constraint satisfaction approach

Artificial Intelligence in Medicine — Sun, 01 Nov 2009 00:00:00 +0100

Conclusion: The proposal presented herein for describing monitoring criteria, comprising the MFTP model and TRACE, permits the supervision of monitoring criteria that cannot be represented by means of thresholds, and makes it possible to construct alarms that give a rate of false positives far below that for threshold alarms. (Source: Artificial Intelligence in Medicine)

Impact of censoring on learning Bayesian networks in survival modelling

Artificial Intelligence in Medicine — Sun, 01 Nov 2009 00:00:00 +0100

Conclusion: Presented methods for learning Bayesian networks from data can be used to learn from censored survival data in the presence of light censoring (up to 20%) by treating censored cases as event-free. Given intermediate or heavy censoring, the learnt models become tuned to the majority class and would thus require a different approach. (Source: Artificial Intelligence in Medicine)

Effect of a limited-enforcement intelligent tutoring system in dermatopathology on student errors, goals and solution paths

Artificial Intelligence in Medicine — Sun, 01 Nov 2009 00:00:00 +0100

Conclusions: Students benefit from a limited-enforcement tutoring system that leverages diagnostic algorithms but does not prevent alternative strategies. Even with limited enforcement, students converge toward the optimal solution path. (Source: Artificial Intelligence in Medicine)

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Editorial Board

Artificial Intelligence in Medicine — Sun, 01 Nov 2009 00:00:00 +0100

(Source: Artificial Intelligence in Medicine)

A biosegmentation benchmark for evaluation of bioimage analysis methods

BMC Bioinformatics - Latest articles — Sun, 01 Nov 2009 00:00:00 +0100

Conclusions: This online benchmark will facilitate integration and comparison of image analysis methods for bioimages. While the primary focus is on biological images, we believe that the dataset and infrastructure will be of interest to researchers and developers working with biological image analysis, image segmentation and object tracking in general. (Source: BMC Bioinformatics - Latest articles)

Mathematical Model of the Formation of Morphogen Gradients Through Membrane-Associated Non-receptors.

Bulletin of Mathematical Biology — Sat, 31 Oct 2009 00:00:00 +0100

Authors: Lei J, Song Y The importance of morphogens is a central concept in developmental biology. Multiple-fate patterning and the robustness of the morphogen gradient are essential for embryo development. The ways by which morphogens diffuse from a local source to form long distance gradients can differ from one morphogen to the other, and for the same morphogen in different organs. This paper will study the mechanism by which morphogens diffuse through the aid of membrane-associated non-receptors and will investigate how the membrane-associated non-receptors help the morphogen to form long distance gradients and to achieve good robustness. Such a mechanism has been reported for some morphogens that are rapidly turned over. We will establish a set of reaction-diffusion equations to m...

IEEE/ACM Transactions on Computational Biology and Bioinformatics - October-December 2009 (Vol. 6, No. 4)

IEEE/ACM Transactions on Computational Biology and Bioinformatics — Fri, 30 Oct 2009 16:07:43 +0100

IEEE/ACM Transactions on Computational Biology and Bioinformatics (Source: IEEE/ACM Transactions on Computational Biology and Bioinformatics)

Prediction of hot spot residues at protein-protein interfaces by combining machine learning and energy-based methods

BMC Bioinformatics - Latest articles — Fri, 30 Oct 2009 00:00:00 +0100

Conclusions: We have developed an hybrid scheme in which energy terms are used as input features of machine learning models. This strategy combines the strengths of machine learning and energy-based methods. Although so far these two types of approaches have mainly been applied separately to biomolecular problems, the results of our investigation indicate that there are substantial benefits to be gained by their integration. (Source: BMC Bioinformatics - Latest articles)

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multiplierz: an extensible API based desktop environment for proteomics data analysis

BMC Bioinformatics - Latest articles — Thu, 29 Oct 2009 00:00:00 +0100

Conclusions: Collectively, mzAPI and multiplierz facilitate a wide range of data analysis tasks, spanning technology development to biological annotation, for mass spectrometry-based proteomics research. (Source: BMC Bioinformatics - Latest articles)

A novel R-package graphic user interface for the analysis of metabonomic profiles

BMC Bioinformatics - Latest articles — Thu, 29 Oct 2009 00:00:00 +0100

Conclusions: We made complex multivariate analysis user-friendly for both experienced and novice users, which could help to expand the use of NMR-based metabonomics. (Source: BMC Bioinformatics - Latest articles)

multiplierz: an extensible API based desktop environment for proteomics data analysis

BMC Bioinformatics - Latest articles — Thu, 29 Oct 2009 00:00:00 +0100

Inferring within-patient HIV-1 evolutionary dynamics under anti-HIV therapy using serial virus samples with vSPA

BMC Bioinformatics - Latest articles — Thu, 29 Oct 2009 00:00:00 +0100

Conclusions: Given that many new anti-HIV drugs will be available in the near future, vSPA may be useful for quickly providing information on the acquisition of HIV drug-resistant mutations by monitoring the within-patient HIV evolution under anti-HIV therapy as a computational approach. (Source: BMC Bioinformatics - Latest articles)

BARCRAWL and BARTAB: Software tools for the design and implementation of barcoded primers for highly multiplexed DNA sequencing

BMC Bioinformatics - Latest articles — Thu, 29 Oct 2009 00:00:00 +0100

Conclusions: Barcrawl and bartab can benefit researchers who are engaged in metagenomic projects that employ multiplexed specimen processing. The source code is released under the GNU general public license and can be accessed at http://www.phyloware.com. (Source: BMC Bioinformatics - Latest articles)

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From Microscopic to Macroscopic Descriptions of Cell Migration on Growing Domains.

Bulletin of Mathematical Biology — Wed, 28 Oct 2009 00:00:00 +0100

Authors: Baker RE, Yates CA, Erban R Cell migration and growth are essential components of the development of multicellular organisms. The role of various cues in directing cell migration is widespread, in particular, the role of signals in the environment in the control of cell motility and directional guidance. In many cases, especially in developmental biology, growth of the domain also plays a large role in the distribution of cells and, in some cases, cell or signal distribution may actually drive domain growth. There is an almost ubiquitous use of partial differential equations (PDEs) for modelling the time evolution of cellular density and environmental cues. In the last 20 years, a lot of attention has been devoted to connecting macroscopic PDEs with more detailed microscopic m...

Analysis and comparison of very large metagenomes with fast clustering and functional annotation

BMC Bioinformatics - Latest articles — Wed, 28 Oct 2009 00:00:00 +0100

Conclusions: RAMMCAP is a very fast method that can cluster and annotate one million metagenomic reads in only hundreds of CPU hours. It is available from http://tools.camera.calit2.net/camera/rammcap/. (Source: BMC Bioinformatics - Latest articles)

ArrayMining: a modular web-application for microarray analysis combining ensemble and consensus methods with cross-study normalization

BMC Bioinformatics - Latest articles — Wed, 28 Oct 2009 00:00:00 +0100

Conclusions: ArrayMining.net is a free web-application for microarray analysis combining a broad choice of algorithms based on ensemble and consensus methods, using automatic parameter selection and integration with annotation databases. (Source: BMC Bioinformatics - Latest articles)

Bioinformatics approaches for genomics and post genomics applications of next-generation sequencing.

Briefings in Bioinformatics — Tue, 27 Oct 2009 00:00:00 +0100

Authors: Horner DS, Pavesi G, Castrignanò 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...

Plasma and urine biomarkers in acute viral hepatitis E

Proteome Science — Tue, 27 Oct 2009 00:00:00 +0100

Background: Hepatitis E, caused by the hepatitis E virus (HEV), is endemic to developing countries where it manifests as waterborne outbreaks and sporadic cases. Though generally self-limited with a low mortality rate, some cases progress to fulminant hepatic failure (FHF) with high mortality. With no identified predictive or diagnostic markers, the events leading to disease exacerbation are not known. Our aim is to use proteomic tools to identify biomarkers of acute and fulminant hepatitis E. Results: We analyzed proteins in the plasma and urine of hepatitis E patients and healthy controls by two-dimensional Differential Imaging Gel Electrophoresis (DIGE) and mass spectrometry, and identified over 30 proteins to be differentially expressed during acute hepatitis E. The levels of one plasm...

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phyloXML: XML for evolutionary biology and comparative genomics

BMC Bioinformatics - Latest articles — Tue, 27 Oct 2009 00:00:00 +0100

Conclusions: PhyloXML is an XML language defined by a complete schema in XSD that allows storing and exchanging the structures of evolutionary trees as well as associated data. More information about phyloXML itself, the XSD schema, as well as tools implementing and supporting phyloXML, is available at http://www.phyloxml.org. (Source: BMC Bioinformatics - Latest articles)

Gene ARMADA: an integrated multi-analysis platform for microarray data implemented in MATLAB

BMC Bioinformatics - Latest articles — Tue, 27 Oct 2009 00:00:00 +0100

Conclusions: Gene ARMADA provides a highly adaptable, integrative, yet flexible tool, which can be used for automated quality control, analysis, annotation and visualization of microarray data constituting a starting point for further data interpretation and integration with numerous other tools. (Source: BMC Bioinformatics - Latest articles)

Bayesian modeling of ChIP-chip data using latent variables

BMC Bioinformatics - Latest articles — Mon, 26 Oct 2009 00:00:00 +0100

Conclusions: The Bayesian latent method is successfully applied to real andten simulated datasets, with comparisons with some of the existing Bayesian methods, hidden Markov model methods, and sliding window methods. The numerical results indicate that the Bayesian latent method can outperform other methods, especially when the data contain outliers. (Source: BMC Bioinformatics - Latest articles)

Time warping of evolutionary distant temporal gene expression data based on noise suppression

BMC Bioinformatics - Latest articles — Mon, 26 Oct 2009 00:00:00 +0100

Conclusions: Our alignment-based predictions of differences in the cell cycle phases between the two yeast species were in a good agreement with the existing data, thus supporting the computational strategy adopted in this study. We propose that the existence of the alternative alignments, specific to distinct groups of genes, suggests presence of different synchronization modes between the two organisms and possible functional decoupling of particular physiological gene networks in the course of evolution. (Source: BMC Bioinformatics - Latest articles)

A Structured Threshold Model for Mountain Pine Beetle Outbreak.

Bulletin of Mathematical Biology — Sat, 24 Oct 2009 00:00:00 +0100

Authors: Lewis MA, Nelson W, Xu C A vigor-structured model for mountain pine beetle outbreak dynamics within a forest stand is proposed and analyzed. This model explicitly tracks the changing vigor structure in the stand. All model parameters, other than beetle vigor preference, were determined by fitting model components to empirical data. An abrupt threshold for tree mortality to beetle densities allows for model simplification. Based on initial beetle density, model outcomes vary from decimation of the entire stand in a single year, to inability of the beetles to infect any trees. An intermediate outcome involves an initial infestation which subsequently dies out before the entire stand is killed. A model extension is proposed for dynamics of beetle aggregation. This involves a stoc...

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A structure filter for the Eukaryotic Linear Motif Resource

BMC Bioinformatics - Latest articles — Fri, 23 Oct 2009 23:00:00 +0100

Conclusions: New occurrences of known linear motifs require experimental validation as the bioinformatics tools currently have limited reliability. The ELM structure filter will aid users assessing candidate motifs presenting in globular structural regions. Most importantly, it will help users to decide whether to expend their valuable time and resources on experimental testing of interesting motif candidates. (Source: BMC Bioinformatics - Latest articles)

ISOLATE: a computational strategy for identifying the primary origin of cancers using high-throughput sequencing

Bioinformatics — Fri, 23 Oct 2009 13:34:21 +0100

We present ISOLATE, a new statistical method that simultaneously predicts the primary site of origin of cancers and addresses sample heterogeneity, while taking advantage of new high-throughput sequencing technology that promises to bring higher accuracy and reproducibility to gene expression profiling experiments. ISOLATE makes predictions de novo, without having seen any training expression profiles of cancers with identified origin. Compared with previous methods, ISOLATE is able to predict the primary site of origin, de-convolve and remove the effect of sample heterogeneity and identify differentially expressed genes with higher accuracy, across both synthetic and clinical datasets. Methods such as ISOLATE are invaluable tools for clinicians faced with carcinomas of unknown primary ori...

Increasing the coverage of a metapopulation consensus genome by iterative read mapping and assembly

Bioinformatics — Fri, 23 Oct 2009 13:34:21 +0100

Motivation: Most microbial species can not be cultured in the laboratory. Metagenomic sequencing may still yield a complete genome if the sequenced community is enriched and the sequencing coverage is high. However, the complexity in a natural population may cause the enrichment culture to contain multiple related strains. This diversity can confound existing strict assembly programs and lead to a fragmented assembly, which is unnecessary if we have a related reference genome available that can function as a scaffold. Results: Here, we map short metagenomic sequencing reads from a population of strains to a related reference genome, and compose a genome that captures the consensus of the population's sequences. We show that by iteration of the mapping and assembly procedure, the coverage i...

De novo transcriptome assembly with ABySS

Bioinformatics — Fri, 23 Oct 2009 13:34:21 +0100

Motivation: Whole transcriptome shotgun sequencing data from non-normalized samples offer unique opportunities to study the metabolic states of organisms. One can deduce gene expression levels using sequence coverage as a surrogate, identify coding changes or discover novel isoforms or transcripts. Especially for discovery of novel events, de novo assembly of transcriptomes is desirable. Results: Transcriptome from tumor tissue of a patient with follicular lymphoma was sequenced with 36 base pair (bp) single- and paired-end reads on the Illumina Genome Analyzer II platform. We assembled ~194 million reads using ABySS into 66 921 contigs 100 bp or longer, with a maximum contig length of 10 951 bp, representing over 30 million base pairs of unique transcriptome sequence, or roughly 1% of the...

Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads

Bioinformatics — Fri, 23 Oct 2009 13:34:21 +0100

We present Pindel, a pattern growth approach, to detect breakpoints of large deletions and medium-sized insertions from paired-end short reads. We use both simulated reads and real data to demonstrate the efficiency of the computer program and accuracy of the results. Availability: The binary code and a short user manual can be freely downloaded from http://www.ebi.ac.uk/~kye/pindel/. Contact: k.ye@lumc.nl; zn1@sanger.ac.uk (Source: Bioinformatics)

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A report on the 2009 SIG on short read sequencing and algorithms (Short-SIG)

Bioinformatics — Fri, 23 Oct 2009 13:34:21 +0100

(Source: Bioinformatics)

PathBuilder--open source software for annotating and developing pathway resources

Bioinformatics — Fri, 23 Oct 2009 13:34:21 +0100

Summary: We have developed PathBuilder, an open-source web application to annotate biological information pertaining to signaling pathways and to create web-based pathway resources. PathBuilder enables annotation of molecular events including protein–protein interactions, enzyme–substrate relationships and protein translocation events either manually or through automated importing of data from other databases. Salient features of PathBuilder include automatic validation of data formats, built-in modules for visualization of pathways, automated import of data from other pathway resources, export of data in several standard data exchange formats and an application programming interface for retrieving existing pathway datasets. Availability: PathBuilder is freely available for dow...

Analyzing biological network parameters with CentiScaPe

Bioinformatics — Fri, 23 Oct 2009 13:34:21 +0100

Summary: The increasing availability of large network datasets along with the progresses in experimental high-throughput technologies have prompted the need for tools allowing easy integration of experimental data with data derived form network computational analysis. In order to enrich experimental data with network topological parameters, we have developed the Cytoscape plug-in CentiScaPe. The plug-in computes several network centrality parameters and allows the user to analyze existing relationships between experimental data provided by the users and node centrality values computed by the plug-in. CentiScaPe allows identifying network nodes that are relevant from both experimental and topological viewpoints. CentiScaPe also provides a Boolean logic-based tool that allows easy characteri...

integrOmics: an R package to unravel relationships between two omics datasets

Bioinformatics — Fri, 23 Oct 2009 13:34:20 +0100

Motivation: With the availability of many ‘omics’ data, such as transcriptomics, proteomics or metabolomics, the integrative or joint analysis of multiple datasets from different technology platforms is becoming crucial to unravel the relationships between different biological functional levels. However, the development of such an analysis is a major computational and technical challenge as most approaches suffer from high data dimensionality. New methodologies need to be developed and validated. Results: integrOmics efficiently performs integrative analyses of two types of ‘omics’ variables that are measured on the same samples. It includes a regularized version of canonical correlation analysis to enlighten correlations between two datasets, and a sparse version o...

ERNEST: a toolbox for chemical reaction network theory

Bioinformatics — Fri, 23 Oct 2009 13:34:20 +0100

Summary: ERNEST Reaction Network Equilibria Study Toolbox is a MATLAB package which, by checking various different criteria on the structure of a chemical reaction network, can exclude the multistationarity of the corresponding reaction system. The results obtained are independent of the rate constants of the reactions, and can be used for model discrimination. Availability and Implementation: The software, implemented in MATLAB, is available under the GNU GPL free software license from http://people.sissa.it/~altafini/papers/SoAl09/. It requires the MATLAB Optimization Toolbox. Contact: altafini@sissa.it (Source: Bioinformatics)

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WEbcoli: an interactive and asynchronous web application for in silico design and analysis of genome-scale E.coli model

Bioinformatics — Fri, 23 Oct 2009 13:34:20 +0100

Summary: WEbcoli is a WEb application for in silico designing, analyzing and engineering Escherichia coli metabolism. It is devised and implemented using advanced web technologies, thereby leading to enhanced usability and dynamic web accessibility. As a main feature, the WEbcoli system provides a user-friendly rich web interface, allowing users to virtually design and synthesize mutant strains derived from the genome-scale wild-type E.coli model and to customize pathways of interest through a graph editor. In addition, constraints-based flux analysis can be conducted for quantifying metabolic fluxes and charactering the physiological and metabolic states under various genetic and/or environmental conditions. Availability: WEbcoli is freely accessible at http://webcoli.org. Contact: cheld@...

iBioSim: a tool for the analysis and design of genetic circuits

Bioinformatics — Fri, 23 Oct 2009 13:34:20 +0100

Summary: iBioSim is a tool that supports learning of genetic circuit models, efficient abstraction-based analysis of these models and the design of synthetic genetic circuits. iBioSim includes project management features and a graphical user interface that facilitate the development and maintenance of genetic circuit models as well as both experimental and simulation data records. Availability: iBioSim is available for download for Windows, Linux, and MacOS at http://www.async.ece.utah.edu/iBioSim/ Contact: myers@ece.utah.edu (Source: Bioinformatics)

COMPASS: a program for generating serial samples under an infinite sites model

Bioinformatics — Fri, 23 Oct 2009 13:34:20 +0100

Summary: The program COMPASS can generate samples that have been collected at various points in time from a population that is evolving according to a Wright–Fisher model. The samples are generated using coalescence simulations permitting various demographic scenarios and the program uses an infinite sites model to generate polymorphism data for the samples. By generating serially sampled population-genetic data, COMPASS allows investigating properties of polymorphism data that has been collected at different time points, and aid in making inference from ancient polymorphism data. Availability: The program and the manual are available at: http://www.egs.uu.se/evbiol/Research/JakobssonLab/compass.html Contact: mattias.jakobsson@ebc.uu.se (Source: Bioinformatics)

3D-SURFER: software for high-throughput protein surface comparison and analysis

Bioinformatics — Fri, 23 Oct 2009 13:34:20 +0100

We present 3D-SURFER, a web-based tool designed to facilitate high-throughput comparison and characterization of proteins based on their surface shape. As each protein is effectively represented by a vector of 3D Zernike descriptors, comparison times for a query protein against the entire PDB take, on an average, only a couple of seconds. The web interface has been designed to be as interactive as possible with displays showing animated protein rotations, CATH codes and structural alignments using the CE program. In addition, geometrically interesting local features of the protein surface, such as pockets that often correspond to ligand binding sites as well as protrusions and flat regions can also be identified and visualized. Availability: 3D-SURFER is a web application that can be freel...

Updates to the RMAP short-read mapping software

Bioinformatics — Fri, 23 Oct 2009 13:34:20 +0100

We report on a major new version of the RMAP software for mapping reads from short-read sequencing technology. General improvements to accuracy and space requirements are included, along with novel functionality. Included in the RMAP software package are tools for mapping paired-end reads, mapping using more sophisticated use of quality scores, collecting ambiguous mapping locations and mapping bisulfite-treated reads. Availability: The applications described in this note are available for download at http://www.cmb.usc.edu/people/andrewds/rmap and are distributed as Open Source software under the GPLv3.0. The software has been tested on Linux and OS X platforms. Contact: andrewds@usc.edu; mzhang@cshl.edu The RMAP algorithm was introduced by (Smith et al., 2008) as one of the earliest avai...

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TagDust--a program to eliminate artifacts from next generation sequencing data

Bioinformatics — Fri, 23 Oct 2009 13:34:20 +0100

Motivation: Next-generation parallel sequencing technologies produce large quantities of short sequence reads. Due to experimental procedures various types of artifacts are commonly sequenced alongside the targeted RNA or DNA sequences. Identification of such artifacts is important during the development of novel sequencing assays and for the downstream analysis of the sequenced libraries. Results: Here we present TagDust, a program identifying artifactual sequences in large sequencing runs. Given a user-defined cutoff for the false discovery rate, TagDust identifies all reads explainable by combinations and partial matches to known sequences used during library preparation. We demonstrate the quality of our method on sequencing runs performed on Illumina's Genome Analyzer platform. Availa...

A hypergraph-based learning algorithm for classifying gene expression and arrayCGH data with prior knowledge

Bioinformatics — Fri, 23 Oct 2009 13:34:20 +0100

Motivation: Incorporating biological prior knowledge into predictive models is a challenging data integration problem in analyzing high-dimensional genomic data. We introduce a hypergraph-based semi-supervised learning algorithm called HyperPrior to classify gene expression and array-based comparative genomic hybridization (arrayCGH) data using biological knowledge as constraints on graph-based learning. HyperPrior is a robust two-step iterative method that alternatively finds the optimal labeling of the samples and the optimal weighting of the features, guided by constraints encoding prior knowledge. The prior knowledge for analyzing gene expression data is that cancer-related genes tend to interact with each other in a protein–protein interaction network. Similarly, the prior knowl...

Modified variational Bayes EM estimation of hidden Markov tree model of cell lineages

Bioinformatics — Fri, 23 Oct 2009 13:34:20 +0100

Motivation: Human pluripotent stem cell lines persist in culture as a heterogeneous population of SSEA3 positive and SSEA3 negative cells. Tracking individual stem cells in real time can elucidate the kinetics of cells switching between the SSEA3 positive and negative substates. However, identifying a cell's substate at all time points within a cell lineage tree is technically difficult. Results: A variational Bayesian Expectation Maximization (EM) with smoothed probabilities (VBEMS) algorithm for hidden Markov trees (HMT) is proposed for incomplete tree structured data. The full posterior of the HMT parameters is determined and the underflow problems associated with previous algorithms are eliminated. Example results for the prediction of the types of cells in synthetic and real stem cell...

Accessible methods for the dynamic time-scale decomposition of biochemical systems

Bioinformatics — Fri, 23 Oct 2009 13:34:20 +0100

Motivation: The growing complexity of biochemical models asks for means to rationally dissect the networks into meaningful and rather independent subnetworks. Such foregoing should ensure an understanding of the system without any heuristics employed. Important for the success of such an approach is its accessibility and the clarity of the presentation of the results. Results: In order to achieve this goal, we developed a method which is a modification of the classical approach of time-scale separation. This modified method as well as the more classical approach have been implemented for time-dependent application within the widely used software COPASI. The implementation includes different possibilities for the representation of the results including 3D-visualization. Availability: The me...