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        <title>Bioinformatics via MedWorm.com</title>
        <description>MedWorm.com provides a medical RSS filtering service. Over 6000 RSS medical sources are combined and output via different filters. This feed contains the latest items from the 'Bioinformatics' source.</description>
        <link><![CDATA[http://www.medworm.com/rss/search.php?qu=Bioinformatics&t=Bioinformatics&s=Search&f=source]]></link>
        <lastBuildDate>Mon, 06 Feb 2012 22:09:25 +0100</lastBuildDate>
        <item>
            <title>seeQTL: a searchable database for human eQTLs</title>
            <link>http://www.medworm.com/index.php?rid=5644435&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F451%3Frss%3D1</link>
            <description>Summary: seeQTL is a comprehensive and versatile eQTL database, including various eQTL studies and a meta-analysis of HapMap eQTL information. The database presents eQTL association results in a convenient browser, using both segmented local-association plots and genome-wide Manhattan plots.
Availability and implementation: seeQTL is freely available for non-commercial use at http://www.bios.unc.edu/research/genomic_software/seeQTL/.
Contact: fred_wright@unc.edu; kxia@bios.unc.edu
Supplementary information: Supplementary data are available at Bioinformatics online. (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644435</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644435</guid>        </item>
        <item>
            <title>An infrastructure for ontology-based information systems in biomedicine: RICORDO case study</title>
            <link>http://www.medworm.com/index.php?rid=5644434&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F448%3Frss%3D1</link>
            <description>Summary: The article presents an infrastructure for supporting the semantic interoperability of biomedical resources based on the management (storing and inference-based querying) of their ontology-based annotations. This infrastructure consists of: (i) a repository to store and query ontology-based annotations; (ii) a knowledge base server with an inference engine to support the storage of and reasoning over ontologies used in the annotation of resources; (iii) a set of applications and services allowing interaction with the integrated repository and knowledge base. The infrastructure is being prototyped and developed and evaluated by the RICORDO project in support of the knowledge management of biomedical resources, including physiology and pharmacology models and associated clinical dat...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644434</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644434</guid>        </item>
        <item>
            <title>PathVar: analysis of gene and protein expression variance in cellular pathways using microarray data</title>
            <link>http://www.medworm.com/index.php?rid=5644433&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F446%3Frss%3D1</link>
            <description>Summary: Finding significant differences between the expression levels of genes or proteins across diverse biological conditions is one of the primary goals in the analysis of functional genomics data. However, existing methods for identifying differentially expressed genes or sets of genes by comparing measures of the average expression across predefined sample groups do not detect differential variance in the expression levels across genes in cellular pathways. Since corresponding pathway deregulations occur frequently in microarray gene or protein expression data, we present a new dedicated web application, PathVar, to analyze these data sources. The software ranks pathway-representing gene/protein sets in terms of the differences of the variance in the within-pathway expression levels ...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644433</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644433</guid>        </item>
        <item>
            <title>GWAtoolbox: an R package for fast quality control and handling of genome-wide association studies meta-analysis data</title>
            <link>http://www.medworm.com/index.php?rid=5644432&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F444%3Frss%3D1</link>
            <description>Summary: The GWAtoolbox is an R package that standardizes and accelerates the handling of data from genome-wide association studies (GWAS), particularly in the context of large-scale GWAS meta-analyses. A key feature of GWAtoolbox is its ability to perform quality control (QC) of any number of files in a matter of minutes. The implemented workflow has been structured to check three particular data quality aspects: (i) data formatting, (ii) quality of the GWAS results and (iii) data consistency across studies. Output consists of an extensive list of quality statistics and plots which allow inspection of individual files and between-study comparison to identify systematic bias.
Availability: http://www.eurac.edu/GWAtoolbox
Contact: cfuchsb@umich.edu; daniel.taliun@eurac.edu
Supplementary inf...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644432</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644432</guid>        </item>
        <item>
            <title>MTBindingSim: simulate protein binding to microtubules</title>
            <link>http://www.medworm.com/index.php?rid=5644431&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F441%3Frss%3D1</link>
            <description>Summary: Many protein&amp;ndash;protein interactions are more complex than can be accounted for by 1:1 binding models. However, biochemists have few tools available to help them recognize and predict the behaviors of these more complicated systems, making it difficult to design experiments that distinguish between possible binding models. MTBindingSim provides researchers with an environment in which they can rapidly compare different models of binding for a given scenario. It is written specifically with microtubule polymers in mind, but many of its models apply equally well to any polymer or any protein&amp;ndash;protein interaction. MTBindingSim can thus both help in training intuition about binding models and with experimental design.
Availability and implementation: MTBindingSim is implemente...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644431</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644431</guid>        </item>
        <item>
            <title>DMAN: a Java tool for analysis of multi-well differential scanning fluorimetry experiments</title>
            <link>http://www.medworm.com/index.php?rid=5644430&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F439%3Frss%3D1</link>
            <description>Summary: Differential scanning fluorimetry (DSF) is a rapid technique that can be used in structural biology to study protein&amp;ndash;ligand interactions. We have developed DMAN, a novel tool to analyse multi-well plate data obtained in DSF experiments. DMAN is easy to install and provides a user-friendly interface. Multi-well plate layouts can be designed by the user and experimental data can be annotated and analysed by DMAN according to the specified plate layout. Statistical tests for significance are performed automatically, and graphical tools are also provided to assist in data analysis. The modular concept of this software will allow easy development of other multi-well plate analysis applications in the future.
Availability and implementation: DMAN is implemented in Java to provide ...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644430</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644430</guid>        </item>
        <item>
            <title>SitePainter: a tool for exploring biogeographical patterns</title>
            <link>http://www.medworm.com/index.php?rid=5644429&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F436%3Frss%3D1</link>
            <description>As microbial ecologists take advantage of high-throughput analytical techniques to describe microbial communities across ever-increasing numbers of samples, the need for new analysis tools that reveal the intrinsic spatial patterns and structures of these populations is crucial. Here we present SitePainter, an interactive graphical tool that allows investigators to create or upload pictures of their study site, load diversity analyses data and display both diversity and taxonomy results in a spatial context. Features of SitePainter include: visualizing &amp;alpha; -diversity, using taxonomic summaries; visualizing &amp;beta; -diversity, using results from multidimensional scaling methods; and animating relationships among microbial taxa or pathways overtime. SitePainter thus increases the visual p...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644429</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644429</guid>        </item>
        <item>
            <title>Identification and removal of ribosomal RNA sequences from metatranscriptomes</title>
            <link>http://www.medworm.com/index.php?rid=5644428&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F433%3Frss%3D1</link>
            <description>Summary: Here, we present riboPicker, a robust framework for the rapid, automated identification and removal of ribosomal RNA sequences from metatranscriptomic datasets. The results can be exported for subsequent analysis, and the databases used for the web-based version are updated on a regular basis. riboPicker categorizes rRNA-like sequences and provides graphical visualizations and tabular outputs of ribosomal coverage, alignment results and taxonomic classifications.
Availability and implementation: This open-source application was implemented in Perl and can be used as stand-alone version or accessed online through a user-friendly web interface. The source code, user help and additional information is available at http://ribopicker.sourceforge.net/.
Contact: rschmied@sciences.sdsu.ed...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644428</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644428</guid>        </item>
        <item>
            <title>RRBSMAP: a fast, accurate and user-friendly alignment tool for reduced representation bisulfite sequencing</title>
            <link>http://www.medworm.com/index.php?rid=5644427&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F430%3Frss%3D1</link>
            <description>Summary: Reduced representation bisulfite sequencing (RRBS) is a powerful yet cost-efficient method for studying DNA methylation on a genomic scale. RRBS involves restriction-enzyme digestion, bisulfite conversion and size selection, resulting in DNA sequencing data that require special bioinformatic handling. Here, we describe RRBSMAP, a short-read alignment tool that is designed for handling RRBS data in a user-friendly and scalable way. RRBSMAP uses wildcard alignment, and avoids the need for any preprocessing or post-processing steps. We benchmarked RRBSMAP against a well-validated MAQ-based pipeline for RRBS read alignment and observed similar accuracy but much improved runtime performance, easier handling and better scaling to large sample sets. In summary, RRBSMAP removes bioinforma...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644427</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644427</guid>        </item>
        <item>
            <title>B-SOLANA: an approach for the analysis of two-base encoding bisulfite sequencing data</title>
            <link>http://www.medworm.com/index.php?rid=5644426&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F428%3Frss%3D1</link>
            <description>Summary: Bisulfite sequencing, a combination of bisulfite treatment and high-throughput sequencing, has proved to be a valuable method for measuring DNA methylation at single base resolution. Here, we present B-SOLANA, an approach for the analysis of two-base encoding (colorspace) bisulfite sequencing data on the SOLiD platform of Life Technologies. It includes the alignment of bisulfite sequences and the determination of methylation levels in CpG as well as non-CpG sequence contexts. B-SOLANA enables a fast and accurate analysis of large raw sequence datasets.
Availability and implementation: The source code, released under the GNU GPLv3 licence, is freely available at http://code.google.com/p/bsolana/.
Contact: b.kreck@ikmb.uni-kiel.de
Supplementary information: Supplementary data are av...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644426</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644426</guid>        </item>
        <item>
            <title>NRPSsp: non-ribosomal peptide synthase substrate predictor</title>
            <link>http://www.medworm.com/index.php?rid=5644425&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F426%3Frss%3D1</link>
            <description>Summary: Non-ribosomal peptide synthetases (NRPSs) are multi-modular enzymes, which biosynthesize many important peptide compounds produced by bacteria and fungi. Some studies have revealed that an individual domain within the NRPSs shows significant substrate selectivity. The discovery and characterization of non-ribosomal peptides are of great interest for the biotechnological industries. We have applied computational mining methods in order to build a database of NRPSs modules that bind to specific substrates. We have used this database to build a hidden Markov model predictor of substrates that bind to a given NRPS.
Availability: The database and the predictor are freely available on an easy-to-use website at www.nrpssp.com.
Contact: carlos.prieto@unileon.es
Supplementary information: ...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644425</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644425</guid>        </item>
        <item>
            <title>Control-FREEC: a tool for assessing copy number and allelic content using next-generation sequencing data</title>
            <link>http://www.medworm.com/index.php?rid=5644424&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F423%3Frss%3D1</link>
            <description>Summary: More and more cancer studies use next-generation sequencing (NGS) data to detect various types of genomic variation. However, even when researchers have such data at hand, single-nucleotide polymorphism arrays have been considered necessary to assess copy number alterations and especially loss of heterozygosity (LOH). Here, we present the tool Control-FREEC that enables automatic calculation of copy number and allelic content profiles from NGS data, and consequently predicts regions of genomic alteration such as gains, losses and LOH. Taking as input aligned reads, Control-FREEC constructs copy number and B-allele frequency profiles. The profiles are then normalized, segmented and analyzed in order to assign genotype status (copy number and allelic content) to each genomic region....</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644424</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644424</guid>        </item>
        <item>
            <title>Integrated annotation and analysis of genetic variants from next-generation sequencing studies with variant tools</title>
            <link>http://www.medworm.com/index.php?rid=5644423&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F421%3Frss%3D1</link>
            <description>Motivation: Storing, annotating and analyzing variants from next-generation sequencing projects can be difficult due to the availability of a wide array of data formats, tools and annotation sources, as well as the sheer size of the data files. Useful tools, including the GATK, ANNOVAR and BEDTools can be integrated into custom pipelines for annotating and analyzing sequence variants. However, building flexible pipelines that support the tracking of variants alongside their samples, while enabling updated annotation and reanalyses, is not a simple task.
Results: We have developed variant tools, a flexible annotation and analysis toolset that greatly simplifies the storage, annotation and filtering of variants and the analysis of the underlying samples. variant tools can be used to manage a...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644423</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644423</guid>        </item>
        <item>
            <title>GenomeRunner: automating genome exploration</title>
            <link>http://www.medworm.com/index.php?rid=5644422&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F419%3Frss%3D1</link>
            <description>Motivation: One of the challenges in interpreting high-throughput genomic studies such as a genome-wide associations, microarray or ChIP-seq is their open-ended nature&amp;mdash;once a set of experimentally identified regions is identified as statistically significant, at least two questions arise: (i) besides P-value, do any of these significant regions stand out in terms of biological implications? (ii) Does the set of significant regions, as a whole, have anything in common genome wide? These issues are difficult to address because of the growing number of annotated genomic features (e.g. single nucleotide polymorphisms, transcription factor binding sites, methylation peaks, etc.), and it is difficult to know a priori which features would be most fruitful to analyze. Our goal is to provide ...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644422</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644422</guid>        </item>
        <item>
            <title>PGAP: pan-genomes analysis pipeline</title>
            <link>http://www.medworm.com/index.php?rid=5644421&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F416%3Frss%3D1</link>
            <description>Summary: With the rapid development of DNA sequencing technology, increasing bacteria genome data enable the biologists to dig the evolutionary and genetic information of prokaryotic species from pan-genome sight. Therefore, the high-efficiency pipelines for pan-genome analysis are mostly needed. We have developed a new pan-genome analysis pipeline (PGAP), which can perform five analytic functions with only one command, including cluster analysis of functional genes, pan-genome profile analysis, genetic variation analysis of functional genes, species evolution analysis and function enrichment analysis of gene clusters. PGAP's performance has been evaluated on 11 Streptococcus pyogenes strains.
Availability:PGAP is developed with Perl script on the Linux Platform and the package is freely a...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644421</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644421</guid>        </item>
        <item>
            <title>The Virtual Fly Brain browser and query interface</title>
            <link>http://www.medworm.com/index.php?rid=5644420&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F411%3Frss%3D1</link>
            <description>We present an online resource that provides a convenient way to study and query fly brain anatomy, expression and genetic data. We extended the newly developed BrainName nomenclature for the adult fly brain into a logically structured ontology that relates a comprehensive set of published neuron classes to the brain regions they innervate. The Virtual Fly Brain interface allows users to explore the structure of the Drosophila brain by browsing 3D images of a brain with subregions displayed as coloured overlays. An integrated query mechanism allows complex searches of underlying anatomy, cells, expression and other data from community databases.
Availability: Virtual Fly Brain is freely available online at www.virtualflybrain.org
Contact: jda@inf.ed.ac.uk (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644420</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644420</guid>        </item>
        <item>
            <title>SNPxGE2: a database for human SNP-coexpression associations</title>
            <link>http://www.medworm.com/index.php?rid=5644419&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F403%3Frss%3D1</link>
            <description>Motivation: Recently, gene&amp;ndash;coexpression relationships have been found to be often conditional and dynamic. Many studies have suggested that single nucleotide polymorphisms (SNPs) have impacts on gene expression variations in human populations.
Results: The SNPxGE2 database contains the computationally predicted human SNP&amp;ndash;coexpression associations, i.e. the differential coexpression between two genes is associated with the genotypes of an SNP. These data were generated from a large-scale association study that was based on the HapMap phase I data, which covered 269 individuals from 4 human populations, 556 873 SNPs and 15 000 gene expression profiles. In order to reduce the computational cost, the SNP&amp;ndash;coexpression associations were assessed using gap/substitution models, p...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644419</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644419</guid>        </item>
        <item>
            <title>Integrating human and murine anatomical gene expression data for improved comparisons</title>
            <link>http://www.medworm.com/index.php?rid=5644418&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F397%3Frss%3D1</link>
            <description>Motivation: Information concerning the gene expression pattern in four dimensions (species, genes, anatomy and developmental stage) is crucial for unraveling the roles of genes through time. There are a variety of anatomical gene expression databases, but extracting information from them can be hampered by their diversity and heterogeneity.
Results: aGEM 3.1 (anatomic Gene Expression Mapping) addresses the issues of diversity and heterogeneity of anatomical gene expression databases by integrating six mouse gene expression resources (EMAGE, GXD, GENSAT, Allen Brain Atlas data base, EUREXPRESS and BioGPS) and three human gene expression databases (HUDSEN, Human Protein Atlas and BioGPS). Furthermore, aGEM 3.1 provides new cross analysis tools to bridge these resources.
Availability and impl...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644418</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644418</guid>        </item>
        <item>
            <title>Construction and completion of flux balance models from pathway databases</title>
            <link>http://www.medworm.com/index.php?rid=5644417&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F388%3Frss%3D1</link>
            <description>We present a multiple gap-filling method to accelerate the development of FBA models using a new tool, called MetaFlux, based on mixed integer linear programming (MILP). The method suggests corrections to the sets of reactions, biomass metabolites, nutrients and secretions. The method generates FBA models directly from Pathway/Genome Databases. Thus, FBA models developed in this framework are easily queried and visualized using the Pathway Tools software. Predicted fluxes are more easily comprehended by visualizing them on diagrams of individual metabolic pathways or of metabolic maps. MetaFlux can also remove redundant high-flux loops, solve FBA models once they are generated and model the effects of gene knockouts. MetaFlux has been validated through construction of FBA models for Escher...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644417</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644417</guid>        </item>
        <item>
            <title>Minimal cut sets in a metabolic network are elementary modes in a dual network</title>
            <link>http://www.medworm.com/index.php?rid=5644416&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F381%3Frss%3D1</link>
            <description>Motivation: Elementary modes (EMs) and minimal cut sets (MCSs) provide important techniques for metabolic network modeling. Whereas EMs describe minimal subnetworks that can function in steady state, MCSs are sets of reactions whose removal will disable certain network functions. Effective algorithms were developed for EM computation while calculation of MCSs is typically addressed by indirect methods requiring the computation of EMs as initial step.
Results: In this contribution, we provide a method that determines MCSs directly without calculating the EMs. We introduce a duality framework for metabolic networks where the enumeration of MCSs in the original network is reduced to identifying the EMs in a dual network. As a further extension, we propose a generalization of MCSs in metabolic...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644416</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644416</guid>        </item>
        <item>
            <title>Metscape 2 bioinformatics tool for the analysis and visualization of metabolomics and gene expression data</title>
            <link>http://www.medworm.com/index.php?rid=5644415&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F373%3Frss%3D1</link>
            <description>We describe a new, substantially redesigned version of our tool Metscape that allows users to enter experimental data for metabolites, genes and pathways and display them in the context of relevant metabolic networks. Metscape 2 uses an internal relational database that integrates data from KEGG and EHMN databases. The new version of the tool allows users to identify enriched pathways from expression profiling data, build and analyze the networks of genes and metabolites, and visualize changes in the gene/metabolite data. We demonstrate the applications of Metscape to annotate molecular pathways for human and mouse metabolites implicated in the pathogenesis of sepsis-induced acute lung injury, for the analysis of gene expression and metabolite data from pancreatic ductal adenocarcinoma, an...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644415</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644415</guid>        </item>
        <item>
            <title>Gaussian process modelling for bicoid mRNA regulation in spatio-temporal Bicoid profile</title>
            <link>http://www.medworm.com/index.php?rid=5644414&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F366%3Frss%3D1</link>
            <description>Motivation: Bicoid protein molecules, translated from maternally provided bicoid mRNA, establish a concentration gradient in Drosophila early embryonic development. There is experimental evidence that the synthesis and subsequent destruction of this protein is regulated at source by precise control of the stability of the maternal mRNA. Can we infer the driving function at the source from noisy observations of the spatio-temporal protein profile? We use non-parametric Gaussian process regression for modelling the propagation of Bicoid in the embryo and infer aspects of source regulation as a posterior function.
Results: With synthetic data from a 1D diffusion model with a source simulated to model mRNA stability regulation, our results establish that the Gaussian process method can accurat...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644414</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644414</guid>        </item>
        <item>
            <title>M3: an improved SNP calling algorithm for Illumina BeadArray data</title>
            <link>http://www.medworm.com/index.php?rid=5644413&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F358%3Frss%3D1</link>
            <description>Summary: Genotype calling from high-throughput platforms such as Illumina and Affymetrix is a critical step in data processing, so that accurate information on genetic variants can be obtained for phenotype&amp;ndash;genotype association studies. A number of algorithms have been developed to infer genotypes from data generated through the Illumina BeadStation platform, including GenCall, GenoSNP, Illuminus and CRLMM. Most of these algorithms are built on population-based statistical models to genotype every SNP in turn, such as GenCall with the GenTrain clustering algorithm, and require a large reference population to perform well. These approaches may not work well for rare variants where only a small proportion of the individuals carry the variant. A fundamentally different approach, impleme...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644413</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644413</guid>        </item>
        <item>
            <title>Inhibition of HIV-1 protease: the rigidity perspective</title>
            <link>http://www.medworm.com/index.php?rid=5644412&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F350%3Frss%3D1</link>
            <description>Motivation: HIV-1 protease is a key drug target due to its role in the life cycle of the HIV-1 virus. Rigidity analysis using the software First is a computationally inexpensive method for inferring functional information from protein crystal structures. We evaluate the rigidity of 206 high-resolution (2 &amp;Aring; or better) X-ray crystal structures of HIV-1 protease and compare the effects of different inhibitors binding to the enzyme.
Results: Inhibitor binding has little effect on the overall rigidity of the protein homodimer, including the rigidity of the active site. The principal effect of inhibitor binding on rigidity is to constrain the flexibility of the &amp;beta;-hairpin flaps, which move to allow access to the active site of the enzyme. We show that commercially available antiviral d...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644412</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644412</guid>        </item>
        <item>
            <title>HydroPaCe: understanding and predicting cross-inhibition in serine proteases through hydrophobic patch centroids</title>
            <link>http://www.medworm.com/index.php?rid=5644411&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F342%3Frss%3D1</link>
            <description>Motivation: Protein&amp;ndash;protein interfaces contain important information about molecular recognition. The discovery of conserved patterns is essential for understanding how substrates and inhibitors are bound and for predicting molecular binding. When an inhibitor binds to different enzymes (e.g. dissimilar sequences, structures or mechanisms what we call cross-inhibition), identification of invariants is a difficult task for which traditional methods may fail.
Results: To clarify how cross-inhibition happens, we model the problem, propose and evaluate a methodology called HydroPaCe to detect conserved patterns. Interfaces are modeled as graphs of atomic apolar interactions and hydrophobic patches are computed and summarized by centroids (HP-centroids), and their conservation is detected...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644411</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644411</guid>        </item>
        <item>
            <title>Prediction and analysis of nucleotide-binding residues using sequence and sequence-derived structural descriptors</title>
            <link>http://www.medworm.com/index.php?rid=5644410&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F331%3Frss%3D1</link>
            <description>Motivation: Nucleotides are multifunctional molecules that are essential for numerous biological processes. They serve as sources for chemical energy, participate in the cellular signaling and they are involved in the enzymatic reactions. The knowledge of the nucleotide&amp;ndash;protein interactions helps with annotation of protein functions and finds applications in drug design.
Results: We propose a novel ensemble of accurate high-throughput predictors of binding residues from the protein sequence for ATP, ADP, AMP, GTP and GDP. Empirical tests show that our NsitePred method significantly outperforms existing predictors and approaches based on sequence alignment and residue conservation scoring. The NsitePred accurately finds more binding residues and binding sites and it performs particula...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644410</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644410</guid>        </item>
        <item>
            <title>SCPC: a method to structurally compare protein complexes</title>
            <link>http://www.medworm.com/index.php?rid=5644409&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F324%3Frss%3D1</link>
            <description>Motivation: Protein&amp;ndash;protein interactions play vital functional roles in various biological phenomena. Physical contacts between proteins have been revealed using experimental approaches that have solved the structures of protein complexes at atomic resolution. To examine the huge number of protein complexes available in the Protein Data Bank, an efficient automated method that compares protein complexes is required.
Results: We have developed Structural Comparison of Protein Complexes (SCPC), a novel method to structurally compare protein complexes. SCPC compares the spatial arrangements of subunits in a complex with those in another complex using secondary structure elements. Similar substructures are detected in two protein complexes and the similarity is scored. SCPC was applied t...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644409</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644409</guid>        </item>
        <item>
            <title>Detection of microRNAs in color space</title>
            <link>http://www.medworm.com/index.php?rid=5644408&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F318%3Frss%3D1</link>
            <description>Motivation: Deep sequencing provides inexpensive opportunities to characterize the transcriptional diversity of known genomes. The AB SOLiD technology generates millions of short sequencing reads in color-space; that is, the raw data is a sequence of colors, where each color represents 2 nt and each nucleotide is represented by two consecutive colors. This strategy is purported to have several advantages, including increased ability to distinguish sequencing errors from polymorphisms. Several programs have been developed to map short reads to genomes in color space. However, a number of previously unexplored technical issues arise when using SOLiD technology to characterize microRNAs.
Results: Here we explore these technical difficulties. First, since the sequenced reads are longer than th...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644408</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644408</guid>        </item>
        <item>
            <title>SomaticSniper: identification of somatic point mutations in whole genome sequencing data</title>
            <link>http://www.medworm.com/index.php?rid=5644407&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F311%3Frss%3D1</link>
            <description>Motivation: The sequencing of tumors and their matched normals is frequently used to study the genetic composition of cancer. Despite this fact, there remains a dearth of available software tools designed to compare sequences in pairs of samples and identify sites that are likely to be unique to one sample.
Results: In this article, we describe the mathematical basis of our SomaticSniper software for comparing tumor and normal pairs. We estimate its sensitivity and precision, and present several common sources of error resulting in miscalls.
Availability and implementation: Binaries are freely available for download at http://gmt.genome.wustl.edu/somatic-sniper/current/, implemented in C and supported on Linux and Mac OS X.
Contact: delarson@wustl.edu; lding@wustl.edu
Supplementary informa...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644407</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644407</guid>        </item>
        <item>
            <title>InFiRe -- a novel computational method for the identification of insertion sites in transposon mutagenized bacterial genomes</title>
            <link>http://www.medworm.com/index.php?rid=5644406&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F306%3Frss%3D1</link>
            <description>Motivation: InFiRe, Insertion Finder via Restriction digest, is a novel software tool that allows for the computational identification of transposon insertion sites in known bacterial genome sequences after transposon mutagenesis experiments. The approach is based on the fact that restriction endonuclease digestions of bacterial DNA yield a unique pattern of DNA fragments with defined sizes. Transposon insertion changes the size of the hosting DNA fragment by a known number of base pairs. The exact size of this fragment can be determined by Southern blot hybridization. Subsequently, the position of insertion can be identified with computational analysis. The outlined method provides a solid basis for the establishment of a new high-throughput technology.
Availability and implementation: Th...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644406</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644406</guid>        </item>
        <item>
            <title>A simple statistical test to infer the causality of target/phenotype correlation from small molecule phenotypic screens</title>
            <link>http://www.medworm.com/index.php?rid=5644405&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F3%2F301%3Frss%3D1</link>
            <description>This study indicates that, empowered by appropriate statistical adjustment, small molecule inhibitor perturbation remains a powerful tool to pin down the relevant biomarker for drug safety and efficacy research.
Contact: xin.wei@roche.com
Supplementary information: Supplementary data are available at Bioinformatics online. (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5644405</comments>
            <pubDate>Mon, 30 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5644405</guid>        </item>
        <item>
            <title>Addendum: topology and prediction of RNA pseudoknots</title>
            <link>http://www.medworm.com/index.php?rid=5604893&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F300%3Frss%3D1</link>
            <description>(Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604893</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604893</guid>        </item>
        <item>
            <title>PGDSpider: an automated data conversion tool for connecting population genetics and genomics programs</title>
            <link>http://www.medworm.com/index.php?rid=5604892&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F298%3Frss%3D1</link>
            <description>Summary: The analysis of genetic data often requires a combination of several approaches using different and sometimes incompatible programs. In order to facilitate data exchange and file conversions between population genetics programs, we introduce PGDSpider, a Java program that can read 27 different file formats and export data into 29, partially overlapping, other file formats. The PGDSpider package includes both an intuitive graphical user interface and a command-line version allowing its integration in complex data analysis pipelines.
Availability: PGDSpider is freely available under the BSD 3-Clause license on http://cmpg.unibe.ch/software/PGDSpider/
Contact: heidi.lischer@iee.unibe.ch
Supplementary information: Supplementary data are available at Bioinformatics online. (Source: Bio...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604892</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604892</guid>        </item>
        <item>
            <title>NoRSE: noise reduction and state evaluator for high-frequency single event traces</title>
            <link>http://www.medworm.com/index.php?rid=5604891&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F296%3Frss%3D1</link>
            <description>Summary: NoRSE was developed to analyze high-frequency datasets collected from multistate, dynamic experiments, such as molecular adsorption and desorption onto carbon nanotubes. As technology improves sampling frequency, these stochastic datasets become increasingly large with faster dynamic events. More efficient algorithms are needed to accurately locate the unique states in each time trace. NoRSE adapts and optimizes a previously published noise reduction algorithm and uses a custom peak flagging routine to rapidly identify unique event states. The algorithm is explained using experimental data from our lab and its fitting accuracy and efficiency are then shown with a generalized model of stochastic datasets. The algorithm is compared to another recently published state finding algorit...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604891</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604891</guid>        </item>
        <item>
            <title>Gene set analysis in the cloud</title>
            <link>http://www.medworm.com/index.php?rid=5604890&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F294%3Frss%3D1</link>
            <description>Summary: Cloud computing offers low cost and highly flexible opportunities in bioinformatics. Its potential has already been demonstrated in high-throughput sequence data analysis. Pathway-based or gene set analysis of expression data has received relatively less attention. We developed a gene set analysis algorithm for biomarker identification in the cloud. The resulting tool, YunBe, is ready to use on Amazon Web Services. Moreover, here we compare its performance to those obtained with desktop and computing cluster solutions.
Availability and implementation: YunBe is open-source and freely accessible within the Amazon Elastic MapReduce service at s3n://lrcv-crp-sante/app/yunbe.jar. Source code and user's guidelines can be downloaded from http://tinyurl.com/yunbedownload.
Contact: francis...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604890</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604890</guid>        </item>
        <item>
            <title>A novel and versatile computational tool to model translation</title>
            <link>http://www.medworm.com/index.php?rid=5604889&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F292%3Frss%3D1</link>
            <description>Motivation: Much is now known about the mechanistic details of gene translation. There are also rapid advances in high-throughput technologies to determine quantitative aspects of the system. As a consequence-realistic and system-wide simulation models of translation are now feasible. Such models are also needed as devices to integrate a large volume of highly fragmented data known about translation.
Software: In this application note, we present a novel, highly efficient software tool to model translation. The tool represents the main aspects of translation. Features include a representation of exhaustible tRNA pools, ribosome&amp;ndash;ribosome interactions and differential initiation rates for different mRNA species. The tool is written in Java, and is hence portable and can be parameterize...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604889</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604889</guid>        </item>
        <item>
            <title>Computing graphlet signatures of network nodes and motifs in Cytoscape with GraphletCounter</title>
            <link>http://www.medworm.com/index.php?rid=5604888&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F290%3Frss%3D1</link>
            <description>Summary: Biological network analysis can be enhanced by examining the connections between nodes and the rest of the network. For this purpose we have developed GraphletCounter, an open-source software tool for computing graphlet degree signatures that can operate on its own or as a plug-in to the network analysis environment Cytoscape. A unique characteristic of GraphletCounter is its ability to compute the graphlet signatures of network motifs, which can be specified by files generated by the motif-finding tool mfinder. GraphletCounter displays graphlet signatures for visual inspection within Cytoscape, and can output graphlet data for integration with larger workflows.
Availability and implementation: GraphletCounter is implemented in Java. It can be downloaded from the Cytoscape plugin ...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604888</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604888</guid>        </item>
        <item>
            <title>MSnbase-an R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation</title>
            <link>http://www.medworm.com/index.php?rid=5604887&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F288%3Frss%3D1</link>
            <description>Summary: MSnbase is an R/Bioconductor package for the analysis of quantitative proteomics experiments that use isobaric tagging. It provides an exploratory data analysis framework for reproducible research, allowing raw data import, quality control, visualization, data processing and quantitation. MSnbase allows direct integration of quantitative proteomics data with additional facilities for statistical analysis provided by the Bioconductor project.
Availability: MSnbase is implemented in R (version &amp;ge;2.13.0) and available at the Bioconductor web site (http://www.bioconductor.org/). Vignettes outlining typical workflows, input/output capabilities and detailing underlying infrastructure are included in the package.
Contact: lg390@cam.ac.uk
Supplementary information: Supplementary data ar...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604887</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604887</guid>        </item>
        <item>
            <title>FTSite: high accuracy detection of ligand binding sites on unbound protein structures</title>
            <link>http://www.medworm.com/index.php?rid=5604886&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F286%3Frss%3D1</link>
            <description>We describe an accurate method of binding site identification, namely FTSite. This method is based on experimental evidence that ligand binding sites also bind small organic molecules of various shapes and polarity. The FTSite algorithm does not rely on any evolutionary or statistical information, but achieves near experimental accuracy: it is capable of identifying the binding sites in over 94% of apo proteins from established test sets that have been used to evaluate many other binding site prediction methods.
Availability: FTSite is freely available as a web-based server at http://ftsite.bu.edu.
Contact: vajda@bu.edu; midas@bu.edu
Supplementary information: Supplementary data are available at Bioinformatics online. (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604886</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604886</guid>        </item>
        <item>
            <title>NARWHAL, a primary analysis pipeline for NGS data</title>
            <link>http://www.medworm.com/index.php?rid=5604885&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F284%3Frss%3D1</link>
            <description>Summary: The NARWHAL software pipeline has been developed to automate the primary analysis of Illumina sequencing data. This pipeline combines a new and flexible de-multiplexing tool with open-source aligners and automated quality assessment. The entire pipeline can be run using only one simple sample-sheet for diverse sequencing applications. NARWHAL creates a sample-oriented data structure and outperforms existing tools in speed.
Availability: https://trac.nbic.nl/narwhal/
Contact: w.vanijcken@erasmusmc.nl
Supplementary information: Supplementary data are available at Bioinformatics online. (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604885</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604885</guid>        </item>
        <item>
            <title>GenomicTools: a computational platform for developing high-throughput analytics in genomics</title>
            <link>http://www.medworm.com/index.php?rid=5604884&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F282%3Frss%3D1</link>
            <description>We present GenomicTools, a flexible computational platform, comprising both a command-line set of tools and a C++ API, for the analysis and manipulation of high-throughput sequencing data such as DNA-seq, RNA-seq, ChIP-seq and MethylC-seq. GenomicTools implements a variety of mathematical operations between sets of genomic regions thereby enabling the prototyping of computational pipelines that can address a wide spectrum of tasks ranging from pre-processing and quality control to meta-analyses. Additionally, the GenomicTools platform is designed to analyze large datasets of any size by minimizing memory requirements. In practical applications, where comparable, GenomicTools outperforms existing tools in terms of both time and memory usage.
Availability: The GenomicTools platform (version ...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604884</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604884</guid>        </item>
        <item>
            <title>BadiRate: estimating family turnover rates by likelihood-based methods</title>
            <link>http://www.medworm.com/index.php?rid=5604883&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F279%3Frss%3D1</link>
            <description>Motivation: The comparative analysis of gene gain and loss rates is critical for understanding the role of natural selection and adaptation in shaping gene family sizes. Studying complete genome data from closely related species allows accurate estimation of gene family turnover rates. Current methods and software tools, however, are not well designed for dealing with certain kinds of functional elements, such as microRNAs or transcription factor binding sites.
Results: Here, we describe BadiRate, a new software tool to estimate family turnover rates, as well as the number of elements in internal phylogenetic nodes, by likelihood-based methods and parsimony. It implements two stochastic population models, which provide the appropriate statistical framework for testing hypothesis, such as l...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604883</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604883</guid>        </item>
        <item>
            <title>TREAT: a bioinformatics tool for variant annotations and visualizations in targeted and exome sequencing data</title>
            <link>http://www.medworm.com/index.php?rid=5604882&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F277%3Frss%3D1</link>
            <description>Summary: TREAT (Targeted RE-sequencing Annotation Tool) is a tool for facile navigation and mining of the variants from both targeted resequencing and whole exome sequencing. It provides a rich integration of publicly available as well as in-house developed annotations and visualizations for variants, variant-hosting genes and host-gene pathways.
Availability and implementation: TREAT is freely available to non-commercial users as either a stand-alone annotation and visualization tool, or as a comprehensive workflow integrating sequencing alignment and variant calling. The executables, instructions and the Amazon Cloud Images of TREAT can be downloaded at the website: http://ndc.mayo.edu/mayo/research/biostat/stand-alone-packages.cfm
Contact: Hossain.Asif@mayo.edu; Kocher.JeanPierre@mayo.e...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604882</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604882</guid>        </item>
        <item>
            <title>Novel search method for the discovery of functional relationships</title>
            <link>http://www.medworm.com/index.php?rid=5604881&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F269%3Frss%3D1</link>
            <description>Motivation: Numerous annotations are available that functionally characterize genes and proteins with regard to molecular process, cellular localization, tissue expression, protein domain composition, protein interaction, disease association and other properties. Searching this steadily growing amount of information can lead to the discovery of new biological relationships between genes and proteins. To facilitate the searches, methods are required that measure the annotation similarity of genes and proteins. However, most current similarity methods are focused only on annotations from the Gene Ontology (GO) and do not take other annotation sources into account.
Results: We introduce the new method BioSim that incorporates multiple sources of annotations to quantify the functional similari...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604881</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604881</guid>        </item>
        <item>
            <title>A novel specific edge effect correction method for RNA interference screenings</title>
            <link>http://www.medworm.com/index.php?rid=5604880&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F261%3Frss%3D1</link>
            <description>We report here a novel edge effect correction algorithm suitable for RNA interference (RNAi) screening, because its normalization does not rely on the entire dataset and takes into account the specificities of such a screening process. The proposed method is able to estimate the edge effects for each assay plate individually using the data from a single control column based on diffusion model, and thus targeting a specific but recurrent well-known HTS artefact. This method was first developed and validated using control plates and was then applied to the correction of experimental data generated during a genome-wide siRNA screen aimed at studying HIV&amp;ndash;host interactions. The proposed algorithm was able to correct the edge effect biasing the control data and thus improve assay quality a...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604880</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604880</guid>        </item>
        <item>
            <title>Which species is it? Species-driven gene name disambiguation using random walks over a mixture of adjacency matrices</title>
            <link>http://www.medworm.com/index.php?rid=5604879&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F254%3Frss%3D1</link>
            <description>Motivation: The scientific literature contains a wealth of information about biological systems. Manual curation lacks the scalability to extract this information due to the ever-increasing numbers of papers being published. The development and application of text mining technologies has been proposed as a way of dealing with this problem. However, the inter-species ambiguity of the genomic nomenclature makes mapping of gene mentions identified in text to their corresponding Entrez gene identifiers an extremely difficult task. We propose a novel method, which transforms a MEDLINE record into a mixture of adjacency matrices; by performing a random walkover the resulting graph, we can perform multi-class supervised classification allowing the assignment of taxonomy identifiers to individual ...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604879</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604879</guid>        </item>
        <item>
            <title>Data-driven information retrieval in heterogeneous collections of transcriptomics data links SIM2s to malignant pleural mesothelioma</title>
            <link>http://www.medworm.com/index.php?rid=5604878&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F246%3Frss%3D1</link>
            <description>Motivation: Genome-wide measurement of transcript levels is an ubiquitous tool in biomedical research. As experimental data continues to be deposited in public databases, it is becoming important to develop search engines that enable the retrieval of relevant studies given a query study. While retrieval systems based on meta-data already exist, data-driven approaches that retrieve studies based on similarities in the expression data itself have a greater potential of uncovering novel biological insights.
Results: We propose an information retrieval method based on differential expression. Our method deals with arbitrary experimental designs and performs competitively with alternative approaches, while making the search results interpretable in terms of differential expression patterns. We ...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604878</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604878</guid>        </item>
        <item>
            <title>Wavelet-based image fusion in multi-view three-dimensional microscopy</title>
            <link>http://www.medworm.com/index.php?rid=5604877&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F238%3Frss%3D1</link>
            <description>Motivation: Multi-view microscopy techniques such as Light-Sheet Fluorescence Microscopy (LSFM) are powerful tools for 3D + time studies of live embryos in developmental biology. The sample is imaged from several points of view, acquiring a set of 3D views that are then combined or fused in order to overcome their individual limitations. Views fusion is still an open problem despite recent contributions in the field.
Results: We developed a wavelet-based multi-view fusion method that, due to wavelet decomposition properties, is able to combine the complementary directional information from all available views into a single volume. Our method is demonstrated on LSFM acquisitions from live sea urchin and zebrafish embryos. The fusion results show improved overall contrast and details when co...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604877</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604877</guid>        </item>
        <item>
            <title>Identifying quantitative trait loci via group-sparse multitask regression and feature selection: an imaging genetics study of the ADNI cohort</title>
            <link>http://www.medworm.com/index.php?rid=5604876&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F229%3Frss%3D1</link>
            <description>Motivation: Recent advances in high-throughput genotyping and brain imaging techniques enable new approaches to study the influence of genetic variation on brain structures and functions. Traditional association studies typically employ independent and pairwise univariate analysis, which treats single nucleotide polymorphisms (SNPs) and quantitative traits (QTs) as isolated units and ignores important underlying interacting relationships between the units. New methods are proposed here to overcome this limitation.
Results: Taking into account the interlinked structure within and between SNPs and imaging QTs, we propose a novel Group-Sparse Multi-task Regression and Feature Selection (G-SMuRFS) method to identify quantitative trait loci for multiple disease-relevant QTs and apply it to a st...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604876</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604876</guid>        </item>
        <item>
            <title>Modelling time course gene expression data with finite mixtures of linear additive models</title>
            <link>http://www.medworm.com/index.php?rid=5604875&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F222%3Frss%3D1</link>
            <description>Summary: A model class of finite mixtures of linear additive models is presented. The component-specific parameters in the regression models are estimated using regularized likelihood methods. The advantages of the regularization are that (i) the pre-specified maximum degrees of freedom for the splines is less crucial than for unregularized estimation and that (ii) for each component individually a suitable degree of freedom is selected in an automatic way. The performance is evaluated in a simulation study with artificial data as well as on a yeast cell cycle dataset of gene expression levels over time.
Availability: The latest release version of the R package flexmix is available from CRAN (http://cran.r-project.org/).
Contact: Bettina.Gruen@jku.at (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604875</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604875</guid>        </item>
        <item>
            <title>Identification of context-specific gene regulatory networks with GEMULA--gene expression modeling using LAsso</title>
            <link>http://www.medworm.com/index.php?rid=5604874&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F214%3Frss%3D1</link>
            <description>Motivation: Gene regulatory networks, in which edges between nodes describe interactions between transcriptional regulators and their target genes, determine the coordinated spatiotemporal expression of genes. Especially in higher organisms, context-specific combinatorial regulation by transcription factors (TFs) is believed to determine cellular states and fates. TF&amp;ndash;target gene interactions can be studied using high-throughput techniques such as ChIP-chip or ChIP-Seq. These experiments are time and cost intensive, and further limited by, for instance, availability of high affinity TF antibodies. Hence, there is a practical need for methods that can predict TF&amp;ndash;TF and TF&amp;ndash;target gene interactions in silico, i.e. from gene expression and DNA sequence data alone. We propose G...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604874</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604874</guid>        </item>
        <item>
            <title>Discovering transcription factor regulatory targets using gene expression and binding data</title>
            <link>http://www.medworm.com/index.php?rid=5604873&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F206%3Frss%3D1</link>
            <description>We present EMBER (Expectation Maximization of Binding and Expression pRofiles), a method that integrates high-throughput binding data (e.g. ChIP-chip or ChIP-seq) with gene expression data (e.g. DNA microarray) via an unsupervised machine learning algorithm for inferring the gene targets of sets of TF binding sites. Genes selected are those that match overrepresented expression patterns, which can be used to provide information about multiple TF regulatory modes. We apply the method to genome-wide human breast cancer data and demonstrate that EMBER confirms a role for the TFs estrogen receptor alpha, retinoic acid receptors alpha and gamma in breast cancer development, whereas the conventional approach of assigning regulatory targets based on proximity does not. Additionally, we compare se...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604873</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604873</guid>        </item>
        <item>
            <title>MetalionRNA: computational predictor of metal-binding sites in RNA structures</title>
            <link>http://www.medworm.com/index.php?rid=5604872&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F198%3Frss%3D1</link>
            <description>Motivation: Metal ions are essential for the folding of RNA molecules into stable tertiary structures and are often involved in the catalytic activity of ribozymes. However, the positions of metal ions in RNA 3D structures are difficult to determine experimentally. This motivated us to develop a computational predictor of metal ion sites for RNA structures.
Results: We developed a statistical potential for predicting positions of metal ions (magnesium, sodium and potassium), based on the analysis of binding sites in experimentally solved RNA structures. The MetalionRNA program is available as a web server that predicts metal ions for RNA structures submitted by the user.
Availability: The MetalionRNA web server is accessible at http://metalionrna.genesilico.pl/.
Contact: iamb@genesilico.pl...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604872</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604872</guid>        </item>
        <item>
            <title>Fast computation of minimum hybridization networks</title>
            <link>http://www.medworm.com/index.php?rid=5604871&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F191%3Frss%3D1</link>
            <description>We describe how to compute a representative set of minimum hybridization networks for two given bifurcating input trees, using a parallel algorithm and provide a user-friendly implementation. A simulation study suggests that our program performs significantly better than existing software on biologically relevant data. Finally, we demonstrate the application of such methods in the context of the evolution of the Aegilops/Triticum genera.
Availability and implementation: The algorithm is implemented in the program Dendroscope 3, which is freely available from www.dendroscope.org and runs on all three major operating systems.
Contact: scornava@informatik.uni-tuebingen.de; huson@informatik.uni-tuebingen.de
Supplementary information: Supplementary data are available at Bioinformatics online. (...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604871</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604871</guid>        </item>
        <item>
            <title>PSICOV: precise structural contact prediction using sparse inverse covariance estimation on large multiple sequence alignments</title>
            <link>http://www.medworm.com/index.php?rid=5604870&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F184%3Frss%3D1</link>
            <description>Motivation: The accurate prediction of residue&amp;ndash;residue contacts, critical for maintaining the native fold of a protein, remains an open problem in the field of structural bioinformatics. Interest in this long-standing problem has increased recently with algorithmic improvements and the rapid growth in the sizes of sequence families. Progress could have major impacts in both structure and function prediction to name but two benefits. Sequence-based contact predictions are usually made by identifying correlated mutations within multiple sequence alignments (MSAs), most commonly through the information-theoretic approach of calculating mutual information between pairs of sites in proteins. These predictions are often inaccurate because the true covariation signal in the MSA is often mas...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604870</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604870</guid>        </item>
        <item>
            <title>Inferring sequence regions under functional divergence in duplicate genes</title>
            <link>http://www.medworm.com/index.php?rid=5604869&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F176%3Frss%3D1</link>
            <description>Motivation: A number of statistical phylogenetic methods have been proposed to identify type-I functional divergence in duplicate genes by detecting heterogeneous substitution rates in phylogenetic trees. A common disadvantage of the existing methods is that autocorrelation of substitution rates along sequences is not modeled. This reduces the power of existing methods to identify regions under functional divergence.
Results: We design a phylogenetic hidden Markov model to identify protein regions relevant to type-I functional divergence. A C++ program, HMMDiverge, has been developed to estimate model parameters and to identify regions under type-I functional divergence. Simulations demonstrate that HMMDiverge can successfully identify protein regions under type-I functional divergence unl...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604869</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604869</guid>        </item>
        <item>
            <title>Feature-based classifiers for somatic mutation detection in tumour-normal paired sequencing data</title>
            <link>http://www.medworm.com/index.php?rid=5604868&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F167%3Frss%3D1</link>
            <description>We present the comparison of four standard supervised machine learning algorithms for the purpose of somatic SNV prediction in tumour/normal NGS experiments. To evaluate these approaches (random forest, Bayesian additive regression tree, support vector machine and logistic regression), we constructed 106 features representing 3369 candidate somatic SNVs from 48 breast cancer genomes, originally predicted with naive methods and subsequently revalidated to establish ground truth labels. We trained the classifiers on this data (consisting of 1015 true somatic mutations and 2354 non-somatic mutation positions) and conducted a rigorous evaluation of these methods using a cross-validation framework and hold-out test NGS data from both exome capture and whole genome shotgun platforms. All learnin...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604868</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604868</guid>        </item>
        <item>
            <title>Using Sybil for interactive comparative genomics of microbes on the web</title>
            <link>http://www.medworm.com/index.php?rid=5604867&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F160%3Frss%3D1</link>
            <description>We describe a new version of the Sybil software package and its application to the important human pathogen Streptococcus pneumoniae. This new software provides a feature-rich set of comparative genomics tools for inspection of multiple genome structures, mining of orthologous gene families and identification of potential vaccine candidates.
Availability: The S.pneumoniae resource is online at http://strepneumo-sybil.igs.umaryland.edu. The software, database and website are available for download as a portable virtual machine and from http://sourceforge.net/projects/sybil.
Contact: driley@som.umaryland.edu
Supplementary information: Supplementary data are available at Bioinformatics online. (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604867</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604867</guid>        </item>
        <item>
            <title>FSR: feature set reduction for scalable and accurate multi-class cancer subtype classification based on copy number</title>
            <link>http://www.medworm.com/index.php?rid=5604866&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F2%2F151%3Frss%3D1</link>
            <description>Motivation: Feature selection is a key concept in machine learning for microarray datasets, where features represented by probesets are typically several orders of magnitude larger than the available sample size. Computational tractability is a key challenge for feature selection algorithms in handling very high-dimensional datasets beyond a hundred thousand features, such as in datasets produced on single nucleotide polymorphism microarrays. In this article, we present a novel feature set reduction approach that enables scalable feature selection on datasets with hundreds of thousands of features and beyond. Our approach enables more efficient handling of higher resolution datasets to achieve better disease subtype classification of samples for potentially more accurate diagnosis and prog...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5604866</comments>
            <pubDate>Mon, 16 Jan 2012 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5604866</guid>        </item>
        <item>
            <title>Sensitive and fast mapping of di-base encoded reads</title>
            <link>http://www.medworm.com/index.php?rid=5534431&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F150%3Frss%3D1</link>
            <description>(Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534431</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534431</guid>        </item>
        <item>
            <title>Automated workflows for accurate mass-based putative metabolite identification in LC/MS-derived metabolomic datasets</title>
            <link>http://www.medworm.com/index.php?rid=5534430&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F149%3Frss%3D1</link>
            <description>(Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534430</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534430</guid>        </item>
        <item>
            <title>Response: an empirical comparison of several recent epistatic interaction detection methods</title>
            <link>http://www.medworm.com/index.php?rid=5534429&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F147%3Frss%3D1</link>
            <description>Contact: fayue1015@gmail.com (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534429</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534429</guid>        </item>
        <item>
            <title>Comments on 'An empirical comparison of several recent epistatic interaction detection methods'</title>
            <link>http://www.medworm.com/index.php?rid=5534428&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F145%3Frss%3D1</link>
            <description>Contact: eeyu@ust.hk (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534428</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534428</guid>        </item>
        <item>
            <title>AURA: Atlas of UTR Regulatory Activity</title>
            <link>http://www.medworm.com/index.php?rid=5534427&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F142%3Frss%3D1</link>
            <description>Summary: The Atlas of UTR Regulatory Activity (AURA) is a manually curated and comprehensive catalog of human mRNA untranslated regions (UTRs) and UTR regulatory annotations. Through its intuitive web interface, it provides full access to a wealth of information on UTRs that integrates phylogenetic conservation, RNA sequence and structure data, single nucleotide variation, gene expression and gene functional descriptions from literature and specialized databases.
Availability: http://aura.science.unitn.it
Contact: aura@science.unitn.it; dassi@science.unitn
Supplementary information: Supplementary data are available at Bioinformatics online. (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534427</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534427</guid>        </item>
        <item>
            <title>PubChem promiscuity: a web resource for gathering compound promiscuity data from PubChem</title>
            <link>http://www.medworm.com/index.php?rid=5534426&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F140%3Frss%3D1</link>
            <description>Summary: Promiscuity counts allow for a better understanding of a compound's assay activity profile and drug potential. Although PubChem contains a vast amount of compound and assay data, it currently does not have a convenient or efficient method to obtain in-depth promiscuity counts for compounds. PubChem promiscuity fills this gap. It is a Java servlet that uses NCBI Entrez (eUtils) web services to interact with PubChem and provide promiscuity counts in a variety of categories along with compound descriptors, including PAINS-based functional group detection.
Availability:http://chemutils.florida.scripps.edu/pcpromiscuity
Contact:southern@scripps.edu (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534426</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534426</guid>        </item>
        <item>
            <title>CellAnimation: an open source MATLAB framework for microscopy assays</title>
            <link>http://www.medworm.com/index.php?rid=5534425&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F138%3Frss%3D1</link>
            <description>Motivation: Advances in microscopy technology have led to the creation of high-throughput microscopes that are capable of generating several hundred gigabytes of images in a few days. Analyzing such wealth of data manually is nearly impossible and requires an automated approach. There are at present a number of open-source and commercial software packages that allow the user to apply algorithms of different degrees of sophistication to the images and extract desired metrics. However, the types of metrics that can be extracted are severely limited by the specific image processing algorithms that the application implements, and by the expertise of the user. In most commercial software, code unavailability prevents implementation by the end user of newly developed algorithms better suited for...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534425</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534425</guid>        </item>
        <item>
            <title>MR-Tandem: parallel X!Tandem using Hadoop MapReduce on Amazon Web Services</title>
            <link>http://www.medworm.com/index.php?rid=5534424&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F136%3Frss%3D1</link>
            <description>Summary: MR-Tandem adapts the popular X!Tandem peptide search engine to work with Hadoop MapReduce for reliable parallel execution of large searches. MR-Tandem runs on any Hadoop cluster but offers special support for Amazon Web Services for creating inexpensive on-demand Hadoop clusters, enabling search volumes that might not otherwise be feasible with the compute resources a researcher has at hand. MR-Tandem is designed to drop in wherever X!Tandem is already in use and requires no modification to existing X!Tandem parameter files, and only minimal modification to X!Tandem-based workflows.
Availability and implementation: MR-Tandem is implemented as a lightly modified X!Tandem C++ executable and a Python script that drives Hadoop clusters including Amazon Web Services (AWS) Elastic Map R...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534424</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534424</guid>        </item>
        <item>
            <title>A robust clustering algorithm for identifying problematic samples in genome-wide association studies</title>
            <link>http://www.medworm.com/index.php?rid=5534423&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F134%3Frss%3D1</link>
            <description>Summary: High-throughput genotyping arrays provide an efficient way to survey single nucleotide polymorphisms (SNPs) across the genome in large numbers of individuals. Downstream analysis of the data, for example in genome-wide association studies (GWAS), often involves statistical models of genotype frequencies across individuals. The complexities of the sample collection process and the potential for errors in the experimental assay can lead to biases and artefacts in an individual's inferred genotypes. Rather than attempting to model these complications, it has become a standard practice to remove individuals whose genome-wide data differ from the sample at large. Here we describe a simple, but robust, statistical algorithm to identify samples with atypical summaries of genome-wide vari...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534423</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534423</guid>        </item>
        <item>
            <title>QuRe: software for viral quasispecies reconstruction from next-generation sequencing data</title>
            <link>http://www.medworm.com/index.php?rid=5534422&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F132%3Frss%3D1</link>
            <description>Summary: Next-generation sequencing (NGS) is an ideal framework for the characterization of highly variable pathogens, with a deep resolution able to capture minority variants. However, the reconstruction of all variants of a viral population infecting a host is a challenging task for genome regions larger than the average NGS read length. QuRe is a program for viral quasispecies reconstruction, specifically developed to analyze long read (&amp;gt;100 bp) NGS data. The software performs alignments of sequence fragments against a reference genome, finds an optimal division of the genome into sliding windows based on coverage and diversity and attempts to reconstruct all the individual sequences of the viral quasispecies&amp;mdash;along with their prevalence&amp;mdash;using a heuristic algorithm, which ...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534422</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534422</guid>        </item>
        <item>
            <title>AMPA: an automated web server for prediction of protein antimicrobial regions</title>
            <link>http://www.medworm.com/index.php?rid=5534421&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F130%3Frss%3D1</link>
            <description>Summary: AMPA is a web application for assessing the antimicrobial domains of proteins, with a focus on the design on new antimicrobial drugs. The application provides fast discovery of antimicrobial patterns in proteins that can be used to develop new peptide-based drugs against pathogens. Results are shown in a user-friendly graphical interface and can be downloaded as raw data for later examination.
Availability: AMPA is freely available on the web at http://tcoffee.crg.cat/apps/ampa. The source code is also available in the web.
Contact: marc.torrent@upf.edu; david.andreu@upf.edu
Supplementary information: Supplementary data are available at Bioinformatics online. (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534421</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534421</guid>        </item>
        <item>
            <title>Dragon PolyA Spotter: predictor of poly(A) motifs within human genomic DNA sequences</title>
            <link>http://www.medworm.com/index.php?rid=5534420&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F127%3Frss%3D1</link>
            <description>Motivation: Recognition of poly(A) signals in mRNA is relatively straightforward due to the presence of easily recognizable polyadenylic acid tail. However, the task of identifying poly(A) motifs in the primary genomic DNA sequence that correspond to poly(A) signals in mRNA is a far more challenging problem. Recognition of poly(A) signals is important for better gene annotation and understanding of the gene regulation mechanisms. In this work, we present one such poly(A) motif prediction method based on properties of human genomic DNA sequence surrounding a poly(A) motif. These properties include thermodynamic, physico-chemical and statistical characteristics. For predictions, we developed Artificial Neural Network and Random Forest models. These models are trained to recognize 12 most com...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534420</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534420</guid>        </item>
        <item>
            <title>RAPSearch2: a fast and memory-efficient protein similarity search tool for next-generation sequencing data</title>
            <link>http://www.medworm.com/index.php?rid=5534419&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F125%3Frss%3D1</link>
            <description>Summary: With the wide application of next-generation sequencing (NGS) techniques, fast tools for protein similarity search that scale well to large query datasets and large databases are highly desirable. In a previous work, we developed RAPSearch, an algorithm that achieved a ~20&amp;ndash;90-fold speedup relative to BLAST while still achieving similar levels of sensitivity for short protein fragments derived from NGS data. RAPSearch, however, requires a substantial memory footprint to identify alignment seeds, due to its use of a suffix array data structure. Here we present RAPSearch2, a new memory-efficient implementation of the RAPSearch algorithm that uses a collision-free hash table to index a similarity search database. The utilization of an optimized data structure further speeds up t...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534419</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534419</guid>        </item>
        <item>
            <title>rNA: a fast and accurate short reads numerical aligner</title>
            <link>http://www.medworm.com/index.php?rid=5534418&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F123%3Frss%3D1</link>
            <description>We present a major update to our rNA (randomized Numerical Aligner) tool. The main feature of rNA is the fact that it achieves an accuracy greater than the majority of other tools in a feasible amount of time. rNA executables and source codes are freely downloadable at http://iga-rna.sourceforge.net/.
Contact: vezzi@appliedgenomics.org; delfabbro@appliedgenomics.org
Supplementary information:Supplementary data are available at Bioinformatics online. (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534418</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534418</guid>        </item>
        <item>
            <title>Detecting differential binding of transcription factors with ChIP-seq</title>
            <link>http://www.medworm.com/index.php?rid=5534417&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F121%3Frss%3D1</link>
            <description>Summary: Increasing number of ChIP-seq experiments are investigating transcription factor binding under multiple experimental conditions, for example, various treatment conditions, several distinct time points and different treatment dosage levels. Hence, identifying differential binding sites across multiple conditions is of practical importance in biological and medical research. To this end, we have developed a powerful and flexible program, called DBChIP, to detect differentially bound sharp binding sites across multiple conditions, with or without matching control samples. By assigning uncertainty measure to the putative differential binding sites, DBChIP facilitates downstream analysis. DBChIP is implemented in R programming language and can work with a wide range of sequencing file ...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534417</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534417</guid>        </item>
        <item>
            <title>SVGMap: configurable image browser for experimental data</title>
            <link>http://www.medworm.com/index.php?rid=5534416&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F119%3Frss%3D1</link>
            <description>Summary: Spatial data visualization is very useful to represent biological data and quickly interpret the results. For instance, to show the expression pattern of a gene in different tissues of a fly, an intuitive approach is to draw the fly with the corresponding tissues and color the expression of the gene in each of them. However, the creation of these visual representations may be a burdensome task. Here we present SVGMap, a java application that automatizes the generation of high-quality graphics for singular data items (e.g. genes) and biological conditions. SVGMap contains a browser that allows the user to navigate the different images created and can be used as a web-based results publishing tool.
Availability: SVGMap is freely available as precompiled java package as well as sourc...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534416</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534416</guid>        </item>
        <item>
            <title>MissForest--non-parametric missing value imputation for mixed-type data</title>
            <link>http://www.medworm.com/index.php?rid=5534415&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F112%3Frss%3D1</link>
            <description>Motivation: Modern data acquisition based on high-throughput technology is often facing the problem of missing data. Algorithms commonly used in the analysis of such large-scale data often depend on a complete set. Missing value imputation offers a solution to this problem. However, the majority of available imputation methods are restricted to one type of variable only: continuous or categorical. For mixed-type data, the different types are usually handled separately. Therefore, these methods ignore possible relations between variable types. We propose a non-parametric method which can cope with different types of variables simultaneously.
Results: We compare several state of the art methods for the imputation of missing values. We propose and evaluate an iterative imputation method (miss...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534415</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534415</guid>        </item>
        <item>
            <title>Expression2Kinases: mRNA profiling linked to multiple upstream regulatory layers</title>
            <link>http://www.medworm.com/index.php?rid=5534414&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F105%3Frss%3D1</link>
            <description>Motivation: Genome-wide mRNA profiling provides a snapshot of the global state of cells under different conditions. However, mRNA levels do not provide direct understanding of upstream regulatory mechanisms. Here, we present a new approach called Expression2Kinases (X2K) to identify upstream regulators likely responsible for observed patterns in genome-wide gene expression. By integrating chromatin immuno-precipitation (ChIP)-seq/chip and position weight matrices (PWMs) data, protein&amp;ndash;protein interactions and kinase&amp;ndash;substrate phosphorylation reactions, we can better identify regulatory mechanisms upstream of genome-wide differences in gene expression. We validated X2K by applying it to recover drug targets of food and drug administration (FDA)-approved drugs from drug perturbati...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534414</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534414</guid>        </item>
        <item>
            <title>Inferring gene regulatory networks from gene expression data by path consistency algorithm based on conditional mutual information</title>
            <link>http://www.medworm.com/index.php?rid=5534413&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F98%3Frss%3D1</link>
            <description>Motivation: Reconstruction of gene regulatory networks (GRNs), which explicitly represent the causality of developmental or regulatory process, is of utmost interest and has become a challenging computational problem for understanding the complex regulatory mechanisms in cellular systems. However, all existing methods of inferring GRNs from gene expression profiles have their strengths and weaknesses. In particular, many properties of GRNs, such as topology sparseness and non-linear dependence, are generally in regulation mechanism but seldom are taken into account simultaneously in one computational method.
Results: In this work, we present a novel method for inferring GRNs from gene expression data considering the non-linear dependence and topological structure of GRNs by employing path ...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534413</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534413</guid>        </item>
        <item>
            <title>Protein subcellular localization of fluorescence imagery using spatial and transform domain features</title>
            <link>http://www.medworm.com/index.php?rid=5534412&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F91%3Frss%3D1</link>
            <description>Motivation: Subcellular localization of proteins is one of the most significant characteristics of living cells. Prediction of protein subcellular locations is crucial to the understanding of various protein functions. Therefore, an accurate, computationally efficient and reliable prediction system is required.
Results: In this article, the predictions of various Support Vector Machine (SVM) models have been combined through majority voting. The proposed ensemble SVM-SubLoc has achieved the highest success rates of 99.7% using hybrid features of Haralick textures and local binary patterns (HarLBP), 99.4% using hybrid features of Haralick textures and Local Ternary Patterns (HarLTP). In addition, SVM-SubLoc has yielded 99.0% accuracy using only local ternary patterns (LTPs) based features. ...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534412</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534412</guid>        </item>
        <item>
            <title>Multifunctional proteins revealed by overlapping clustering in protein interaction network</title>
            <link>http://www.medworm.com/index.php?rid=5534411&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F84%3Frss%3D1</link>
            <description>Motivation: Multifunctional proteins perform several functions. They are expected to interact specifically with distinct sets of partners, simultaneously or not, depending on the function performed. Current graph clustering methods usually allow a protein to belong to only one cluster, therefore impeding a realistic assignment of multifunctional proteins to clusters.
Results: Here, we present Overlapping Cluster Generator (OCG), a novel clustering method which decomposes a network into overlapping clusters and which is, therefore, capable of correct assignment of multifunctional proteins. The principle of OCG is to cover the graph with initial overlapping classes that are iteratively fused into a hierarchy according to an extension of Newman's modularity function. By applying OCG to a huma...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534411</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534411</guid>        </item>
        <item>
            <title>Decompositions of large-scale biological systems based on dynamical properties</title>
            <link>http://www.medworm.com/index.php?rid=5534410&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F76%3Frss%3D1</link>
            <description>Motivation: Given a large-scale biological network represented as an influence graph, in this article we investigate possible decompositions of the network aimed at highlighting specific dynamical properties.
Results: The first decomposition we study consists in finding a maximal directed acyclic subgraph of the network, which dynamically corresponds to searching for a maximal open-loop subsystem of the given system. Another dynamical property investigated is strong monotonicity. We propose two methods to deal with this property, both aimed at decomposing the system into strongly monotone subsystems, but with different structural characteristics: one method tends to produce a single large strongly monotone component, while the other typically generates a set of smaller disjoint strongly mo...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534410</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534410</guid>        </item>
        <item>
            <title>Gene Ontology-driven inference of protein-protein interactions using inducers</title>
            <link>http://www.medworm.com/index.php?rid=5534409&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F69%3Frss%3D1</link>
            <description>Motivation: Protein&amp;ndash;protein interactions (PPIs) are pivotal for many biological processes and similarity in Gene Ontology (GO) annotation has been found to be one of the strongest indicators for PPI. Most GO-driven algorithms for PPI inference combine machine learning and semantic similarity techniques. We introduce the concept of inducers as a method to integrate both approaches more effectively, leading to superior prediction accuracies.
Results: An inducer (ULCA) in combination with a Random Forest classifier compares favorably to several sequence-based methods, semantic similarity measures and multi-kernel approaches. On a newly created set of high-quality interaction data, the proposed method achieves high cross-species prediction accuracies (Area under the ROC curve &amp;le; 0.88),...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534409</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534409</guid>        </item>
        <item>
            <title>Using Poisson mixed-effects model to quantify transcript-level gene expression in RNA-Seq</title>
            <link>http://www.medworm.com/index.php?rid=5534408&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F63%3Frss%3D1</link>
            <description>In this study, we propose a Poisson mixed-effects (POME) model to characterize base-level read coverage within each transcript. The underlying expression level is included as a key parameter in this model. Since the proposed model is capable of incorporating base-specific variation as well as between-base dependence that affect read coverage profile throughout the transcript, it can lead to improved quantification of the true underlying expression level.
Availability and implementation: POME can be freely downloaded at http://www.stat.purdue.edu/~yuzhu/pome.html.
Contact: yuzhu@purdue.edu; zhaohui.qin@emory.edu
Supplementary information: Supplementary data are available at Bioinformatics online. (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534408</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534408</guid>        </item>
        <item>
            <title>Epigenetic priors for identifying active transcription factor binding sites</title>
            <link>http://www.medworm.com/index.php?rid=5534407&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F56%3Frss%3D1</link>
            <description>We describe a probabilistic method for combining one or more tracks of epigenetic data with a standard DNA sequence motif model to improve our ability to identify active transcription factor binding sites (TFBSs). We convert each data type into a position-specific probabilistic prior and combine these priors with a traditional probabilistic motif model to compute a log-posterior odds score. Our experiments, using histone modifications H3K4me1, H3K4me3, H3K9ac and H3K27ac, as well as DNase I sensitivity, show conclusively that the log-posterior odds score consistently outperforms a simple binary filter based on the same data. We also show that our approach performs competitively with a more complex method, CENTIPEDE, and suggest that the relative simplicity of the log-posterior odds scoring...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534407</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534407</guid>        </item>
        <item>
            <title>Determining the evolutionary history of gene families</title>
            <link>http://www.medworm.com/index.php?rid=5534406&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F48%3Frss%3D1</link>
            <description>Motivation: Recent large-scale studies of individuals within a population have demonstrated that there is widespread variation in copy number in many gene families. In addition, there is increasing evidence that the variation in gene copy number can give rise to substantial phenotypic effects. In some cases, these variations have been shown to be adaptive. These observations show that a full understanding of the evolution of biological function requires an understanding of gene gain and gene loss. Accurate, robust evolutionary models of gain and loss events are, therefore, required.
Results: We have developed weighted parsimony and maximum likelihood methods for inferring gain and loss events. To test these methods, we have used Markov models of gain and loss to simulate data with known pr...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534406</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534406</guid>        </item>
        <item>
            <title>Correcting for cancer genome size and tumour cell content enables better estimation of copy number alterations from next-generation sequence data</title>
            <link>http://www.medworm.com/index.php?rid=5534405&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F40%3Frss%3D1</link>
            <description>Motivation: Comparison of read depths from next-generation sequencing between cancer and normal cells makes the estimation of copy number alteration (CNA) possible, even at very low coverage. However, estimating CNA from patients' tumour samples poses considerable challenges due to infiltration with normal cells and aneuploid cancer genomes. Here we provide a method that corrects contamination with normal cells and adjusts for genomes of different sizes so that the actual copy number of each region can be estimated.
Results: The procedure consists of several steps. First, we identify the multi-modality of the distribution of smoothed ratios. Then we use the estimates of the mean (modes) to identify underlying ploidy and the contamination level, and finally we perform the correction. The re...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534405</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534405</guid>        </item>
        <item>
            <title>A novel structural position-specific scoring matrix for the prediction of protein secondary structures</title>
            <link>http://www.medworm.com/index.php?rid=5534404&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F32%3Frss%3D1</link>
            <description>Motivation: The precise prediction of protein secondary structure is of key importance for the prediction of 3D structure and biological function. Although the development of many excellent methods over the last few decades has allowed the achievement of prediction accuracies of up to 80%, progress seems to have reached a bottleneck, and further improvements in accuracy have proven difficult.
Results: We propose for the first time a structural position-specific scoring matrix (SPSSM), and establish an unprecedented database of 9 million sequences and their SPSSMs. This database, when combined with a purpose-designed BLAST tool, provides a novel prediction tool: SPSSMPred. When the SPSSMPred was validated on a large dataset (10 814 entries), the Q3 accuracy of the protein secondary structur...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534404</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534404</guid>        </item>
        <item>
            <title>Large-scale motif discovery using DNA Gray code and equiprobable oligomers</title>
            <link>http://www.medworm.com/index.php?rid=5534403&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F25%3Frss%3D1</link>
            <description>Motivation: How to find motifs from genome-scale functional sequences, such as all the promoters in a genome, is a challenging problem. Word-based methods count the occurrences of oligomers to detect excessively represented ones. This approach is known to be fast and accurate compared with other methods. However, two problems have hampered the application of such methods to large-scale data. One is the computational cost necessary for clustering similar oligomers, and the other is the bias in the frequency of fixed-length oligomers, which complicates the detection of significant words.
Results: We introduce a method that uses a DNA Gray code and equiprobable oligomers, which solve the clustering problem and the oligomer bias, respectively. Our method can analyze 18 000 sequences of ~1 kbp ...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534403</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534403</guid>        </item>
        <item>
            <title>deepBlockAlign: a tool for aligning RNA-seq profiles of read block patterns</title>
            <link>http://www.medworm.com/index.php?rid=5534402&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F17%3Frss%3D1</link>
            <description>Motivation: High-throughput sequencing methods allow whole transcriptomes to be sequenced fast and cost-effectively. Short RNA sequencing provides not only quantitative expression data but also an opportunity to identify novel coding and non-coding RNAs. Many long transcripts undergo post-transcriptional processing that generates short RNA sequence fragments. Mapped back to a reference genome, they form distinctive patterns that convey information on both the structure of the parent transcript and the modalities of its processing. The miR-miR* pattern from microRNA precursors is the best-known, but by no means singular, example.
Results: deepBlockAlign introduces a two-step approach to align RNA-seq read patterns with the aim of quickly identifying RNAs that share similar processing footpr...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534402</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534402</guid>        </item>
        <item>
            <title>Graph accordance of next-generation sequence assemblies</title>
            <link>http://www.medworm.com/index.php?rid=5534401&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F13%3Frss%3D1</link>
            <description>We describe an algorithm to take advantages of different assembly algorithms or sequencing platforms to improve the quality of next-generation sequence (NGS) assemblies.
Results: The algorithm is implemented as a graph accordance assembly (GAA) program. The algorithm constructs an accordance graph to capture the mapping information between the target and query assemblies. Based on the accordance graph, the contigs or scaffolds of the target assembly can be extended, merged or bridged together. Extra constraints, including gap sizes, mate pairs, scaffold order and orientation, are explored to enforce those accordance operations in the correct context. We applied GAA to various chicken NGS assemblies and the results demonstrate improved contiguity statistics and higher genome and gene covera...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534401</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534401</guid>        </item>
        <item>
            <title>Detecting genome-wide epistases based on the clustering of relatively frequent items</title>
            <link>http://www.medworm.com/index.php?rid=5534400&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F5%3Frss%3D1</link>
            <description>Motivation: In genome-wide association studies (GWAS), up to millions of single nucleotide polymorphisms (SNPs) are genotyped for thousands of individuals. However, conventional single locus-based approaches are usually unable to detect gene&amp;ndash;gene interactions underlying complex diseases. Due to the huge search space for complicated high order interactions, many existing multi-locus approaches are slow and may suffer from low detection power for GWAS.
Results: In this article, we develop a simple, fast and effective algorithm to detect genome-wide multi-locus epistatic interactions based on the clustering of relatively frequent items. Extensive experiments on simulated data show that our algorithm is fast and more powerful in general than some recently proposed methods. On a real geno...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534400</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534400</guid>        </item>
        <item>
            <title>Time-course network analysis reveals TNF-{alpha} can promote G1/S transition of cell cycle in vascular endothelial cells</title>
            <link>http://www.medworm.com/index.php?rid=5534399&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F28%2F1%2F1%3Frss%3D1</link>
            <description>Motivation: Tumor necrosis factor-alpha (TNF-&amp;alpha;), a major inflammatory cytokine, is closely related to several cardiovascular pathological processes. However, its effects on the cell cycle of vascular endothelial cells (VECs) have been the subject of some controversy. To investigate the molecular mechanism underlying this process, we constructed time-course protein&amp;ndash;protein interaction (PPI) networks of TNF-&amp;alpha; induced regulation of cell cycle in VECs using microarray datasets and genome-wide PPI datasets. Then, we analyzed the topological properties of the responsive PPI networks and calculated the node degree and node betweenness centralization of each gene in the networks. We found that p21, p27 and cyclinD1, key genes of the G1/S checkpoint, are in the center of responsiv...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5534399</comments>
            <pubDate>Thu, 22 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5534399</guid>        </item>
        <item>
            <title>BDTcomparator: a program for comparing binary classifiers</title>
            <link>http://www.medworm.com/index.php?rid=5484129&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F24%2F3439%3Frss%3D1</link>
            <description>Summary: The BDTcomparator facilitates the selection of the best performing binary classification model or binary diagnostic procedure from the many possible alternatives by comparing their predictions with a known output, measured with the use of a system recognized as the gold standard. The program calculates the estimates of accuracy, sensitivity, specificity, predictive values and diagnostic likelihood ratios along with appropriate confidence intervals. Furthermore, all pairwise comparisons with respect to the above-mentioned measures are calculated. The formatted results can be exported to a text-file.
Availability and Implementation: BDTcomparator is distributed under the GNU GPLv3 license and is freely available for download from http://www.tox-portal.net. We provide programs for bo...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5484129</comments>
            <pubDate>Tue, 06 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5484129</guid>        </item>
        <item>
            <title>BioPAX support in CellDesigner</title>
            <link>http://www.medworm.com/index.php?rid=5484128&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F24%2F3437%3Frss%3D1</link>
            <description>Motivation: BioPAX is a standard language for representing and exchanging models of biological processes at the molecular and cellular levels. It is widely used by different pathway databases and genomics data analysis software. Currently, the primary source of BioPAX data is direct exports from the curated pathway databases. It is still uncommon for wet-lab biologists to share and exchange pathway knowledge using BioPAX. Instead, pathways are usually represented as informal diagrams in the literature. In order to encourage formal representation of pathways, we describe a software package that allows users to create pathway diagrams using CellDesigner, a user-friendly graphical pathway-editing tool and save the pathway data in BioPAX Level 3 format.
Availability: The plug-in is freely avai...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5484128</comments>
            <pubDate>Tue, 06 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5484128</guid>        </item>
        <item>
            <title>PoPoolation2: identifying differentiation between populations using sequencing of pooled DNA samples (Pool-Seq)</title>
            <link>http://www.medworm.com/index.php?rid=5484127&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F24%2F3435%3Frss%3D1</link>
            <description>Summary: Sequencing pooled DNA samples (Pool-Seq) is the most cost-effective approach for the genome-wide comparison of population samples. Here, we introduce PoPoolation2, the first software tool specifically designed for the comparison of populations with Pool-Seq data. PoPoolation2 implements a range of commonly used measures of differentiation (FST, Fisher's exact test and Cochran-Mantel-Haenszel test) that can be applied on different scales (windows, genes, exons, SNPs). The result may be visualized with the widely used Integrated Genomics Viewer.
Availability and Implementation: PoPoolation2 is implemented in Perl and R. It is freely available on http://code.google.com/p/popoolation2/
Contact: christian.schloetterer@vetmeduni.ac.at
Supplementary Information: Manual: http://code.googl...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5484127</comments>
            <pubDate>Tue, 06 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5484127</guid>        </item>
        <item>
            <title>VizPrimer: a web server for visualized PCR primer design based on known gene structure</title>
            <link>http://www.medworm.com/index.php?rid=5484126&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F24%2F3432%3Frss%3D1</link>
            <description>Summary: The visualization of gene structure plays an important role in polymerase chain reaction (PCR) primer design, especially for eukaryotic genes with a number of splice variants that users need to distinguish between via PCR. Here, we describe a visualized web server for primer design named VizPrimer. It utilizes the new information technology (IT) tools, HTML5 to display gene structure and JavaScript to interact with the users. In VizPrimer, the users can focus their attention on the gene structure and primer design strategy, without wasting time calculating the exon positions of splice variants or manually configuring complicated parameters. In addition, VizPrimer is also suitable for the design of PCR primers for amplifying open reading frames and detecting single nucleotide polym...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5484126</comments>
            <pubDate>Tue, 06 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5484126</guid>        </item>
        <item>
            <title>Enrich: software for analysis of protein function by enrichment and depletion of variants</title>
            <link>http://www.medworm.com/index.php?rid=5484125&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F24%2F3430%3Frss%3D1</link>
            <description>We present Enrich, a tool for analyzing such deep mutational scanning data. Enrich identifies all unique variants (mutants) of a protein in high-throughput sequencing datasets and can correct for sequencing errors using overlapping paired-end reads. Enrich uses the frequency of each variant before and after selection to calculate an enrichment ratio, which is used to estimate fitness. Enrich provides an interactive interface to guide users. It generates user-accessible output for downstream analyses as well as several visualizations of the effects of mutation on function, thereby allowing the user to rapidly quantify and comprehend sequence&amp;ndash;function relationships.
Availability and Implementation: Enrich is implemented in Python and is available under a FreeBSD license at http://depts...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5484125</comments>
            <pubDate>Tue, 06 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5484125</guid>        </item>
        <item>
            <title>Mapping personal functional data to personal genomes</title>
            <link>http://www.medworm.com/index.php?rid=5484124&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F24%2F3427%3Frss%3D1</link>
            <description>Motivation: The sequencing of personal genomes enabled analysis of variation in transcription factor (TF) binding, chromatin structure and gene expression and indicated how they contribute to phenotypic variation. It is hypothesized that using the reference genome for mapping ChIP-seq or RNA-seq reads may introduce errors, especially at polymorphic genomic regions.
Results: We developed a Personal Genome Editor (perEditor) that changes the reference human genome (NCBI36/hg18) into an individual genome, taking into account single nucleotide polymorphisms (SNPs), insertions and deletions, copy number variation, and chromosomal rearrangements. perEditor outputs two alleles (maternal, paternal) of the individual genome that is ready for mapping ChIP-seq and RNA-seq reads, and enabling the anal...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5484124</comments>
            <pubDate>Tue, 06 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5484124</guid>        </item>
        <item>
            <title>Visualization and quality assessment of de novo genome assemblies</title>
            <link>http://www.medworm.com/index.php?rid=5484123&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F24%2F3425%3Frss%3D1</link>
            <description>We present a method to evaluate genome scaffolding by aligning independently obtained transcriptome sequences to the genome and visually summarizing the alignments using the Cytoscape software. Applying this method to the genome of the red fire ant Solenopsis invicta allowed us to identify inconsistencies in 7%, confirm contig order in 20% and extend 16% of scaffolds.
Contact: oksana.ribagrognuz@unil.ch; yannick.wurm@unil.ch
Availability: Scripts that generate tables for visualization in Cytoscape from FASTA sequence and scaffolding information files are publicly available at https://github.com/ksanao/TGNet.
Supplementary Information: Supplementary data are available at Bioinformatics online. (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5484123</comments>
            <pubDate>Tue, 06 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5484123</guid>        </item>
        <item>
            <title>Pybedtools: a flexible Python library for manipulating genomic datasets and annotations</title>
            <link>http://www.medworm.com/index.php?rid=5484122&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F24%2F3423%3Frss%3D1</link>
            <description>Summary: pybedtools is a flexible Python software library for manipulating and exploring genomic datasets in many common formats. It provides an intuitive Python interface that extends upon the popular BEDTools genome arithmetic tools. The library is well documented and efficient, and allows researchers to quickly develop simple, yet powerful scripts that enable complex genomic analyses.
Availability: pybedtools is maintained under the GPL license. Stable versions of pybedtools as well as documentation are available on the Python Package Index at http://pypi.python.org/pypi/pybedtools.
Contact: dalerr@niddk.nih.gov; arq5x@virginia.edu
Supplementary Information: Supplementary data are available at Bioinformatics online. (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5484122</comments>
            <pubDate>Tue, 06 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5484122</guid>        </item>
        <item>
            <title>Cascade detection for the extraction of localized sequence features; specificity results for HIV-1 protease and structure-function results for the Schellman loop</title>
            <link>http://www.medworm.com/index.php?rid=5484121&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F24%2F3415%3Frss%3D1</link>
            <description>Motivation: The extraction of the set of features most relevant to function from classified biological sequence sets is still a challenging problem. A central issue is the determination of expected counts for higher order features so that artifact features may be screened.
Results: Cascade detection (CD), a new algorithm for the extraction of localized features from sequence sets, is introduced. CD is a natural extension of the proportional modeling techniques used in contingency table analysis into the domain of feature detection. The algorithm is successfully tested on synthetic data and then applied to feature detection problems from two different domains to demonstrate its broad utility. An analysis of HIV-1 protease specificity reveals patterns of strong first-order features that grou...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5484121</comments>
            <pubDate>Tue, 06 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5484121</guid>        </item>
        <item>
            <title>A system-level approach for deciphering the transcriptional response to prion infection</title>
            <link>http://www.medworm.com/index.php?rid=5484120&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F24%2F3407%3Frss%3D1</link>
            <description>Motivation: Deciphering the response of a complex biological system to an insulting event, at the gene expression level, requires adopting theoretical models that are more sophisticated than a one-to-one comparison (i.e. t-test). Here, we investigate the ability of a novel reverse engineering approach (System Response Inference) to unveil non-obvious transcriptional signatures of the system response induced by prion infection.
Results: To this end, we analyze previously published gene expression data, from which we extrapolate a putative full-scale model of transcriptional gene&amp;ndash;gene dependencies in the mouse central nervous system. Then, we use this nominal model to interpret the gene expression changes caused by prion replication, aiming at selecting the genes primarily influenced b...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5484120</comments>
            <pubDate>Tue, 06 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5484120</guid>        </item>
        <item>
            <title>Optimized application of penalized regression methods to diverse genomic data</title>
            <link>http://www.medworm.com/index.php?rid=5484119&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F24%2F3399%3Frss%3D1</link>
            <description>Motivation: Penalized regression methods have been adopted widely for high-dimensional feature selection and prediction in many bioinformatic and biostatistical contexts. While their theoretical properties are well-understood, specific methodology for their optimal application to genomic data has not been determined.
Results: Through simulation of contrasting scenarios of correlated high-dimensional survival data, we compared the LASSO, Ridge and Elastic Net penalties for prediction and variable selection. We found that a 2D tuning of the Elastic Net penalties was necessary to avoid mimicking the performance of LASSO or Ridge regression. Furthermore, we found that in a simulated scenario favoring the LASSO penalty, a univariate pre-filter made the Elastic Net behave more like Ridge regress...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5484119</comments>
            <pubDate>Tue, 06 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5484119</guid>        </item>
        <item>
            <title>Automatic rebuilding and optimization of crystallographic structures in the Protein Data Bank</title>
            <link>http://www.medworm.com/index.php?rid=5484118&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F24%2F3392%3Frss%3D1</link>
            <description>Motivation: Macromolecular crystal structures in the Protein Data Bank (PDB) are a key source of structural insight into biological processes. These structures, some &amp;gt;30 years old, were constructed with methods of their era. With PDB_REDO, we aim to automatically optimize these structures to better fit their corresponding experimental data, passing the benefits of new methods in crystallography on to a wide base of non-crystallographer structure users.
Results: We developed new algorithms to allow automatic rebuilding and remodeling of main chain peptide bonds and side chains in crystallographic electron density maps, and incorporated these and further enhancements in the PDB_REDO procedure. Applying the updated PDB_REDO to the oldest, but also to some of the newest models in the PDB, c...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5484118</comments>
            <pubDate>Tue, 06 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5484118</guid>        </item>
        <item>
            <title>STRIKE: evaluation of protein MSAs using a single 3D structure</title>
            <link>http://www.medworm.com/index.php?rid=5484117&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F24%2F3385%3Frss%3D1</link>
            <description>Motivation: Evaluating alternative multiple protein sequence alignments is an important unsolved problem in Biology. The most accurate way of doing this is to use structural information. Unfortunately, most methods require at least two structures to be embedded in the alignment, a condition rarely met when dealing with standard datasets.
Result: We developed STRIKE, a method that determines the relative accuracy of two alternative alignments of the same sequences using a single structure. We validated our methodology on three commonly used reference datasets (BAliBASE, Homestrad and Prefab). Given two alignments, STRIKE manages to identify the most accurate one in 70% of the cases on average. This figure increases to 79% when considering very challenging datasets like the RV11 category of ...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5484117</comments>
            <pubDate>Tue, 06 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5484117</guid>        </item>
        <item>
            <title>Predicting residue-residue contacts using random forest models</title>
            <link>http://www.medworm.com/index.php?rid=5484116&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F24%2F3379%3Frss%3D1</link>
            <description>Motivation: Protein residue&amp;ndash;residue contact prediction can be useful in predicting protein 3D structures. Current algorithms for such a purpose leave room for improvement.
Results: We develop ProC_S3, a set of Random Forest algorithm-based models, for predicting residue&amp;ndash;residue contact maps. The models are constructed based on a collection of 1490 non&amp;ndash;redundant, high-resolution protein structures using &amp;gt;1280 sequence-based features. A new amino acid residue contact propensity matrix and a new set of seven amino acid groups based on contact preference are developed and used in ProC_S3. ProC_S3 delivers a 3-fold cross-validated accuracy of 26.9% with coverage of 4.7% for top L/5 predictions (L is the number of residues in a protein) of long-range contacts (sequence separ...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5484116</comments>
            <pubDate>Tue, 06 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5484116</guid>        </item>
        <item>
            <title>An automatic method for CASP9 free modeling structure prediction assessment</title>
            <link>http://www.medworm.com/index.php?rid=5484115&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F24%2F3371%3Frss%3D1</link>
            <description>Motivation: Manual inspection has been applied to and is well accepted for assessing critical assessment of protein structure prediction (CASP) free modeling (FM) category predictions over the years. Such manual assessment requires expertise and significant time investment, yet has the problems of being subjective and unable to differentiate models of similar quality. It is beneficial to incorporate the ideas behind manual inspection to an automatic score system, which could provide objective and reproducible assessment of structure models.
Results: Inspired by our experience in CASP9 FM category assessment, we developed an automatic superimposition independent method named Quality Control Score (QCS) for structure prediction assessment. QCS captures both global and local structural featur...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5484115</comments>
            <pubDate>Tue, 06 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5484115</guid>        </item>
        <item>
            <title>The design of optimal therapeutic small interfering RNA molecules targeting diverse strains of influenza A virus</title>
            <link>http://www.medworm.com/index.php?rid=5484114&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F24%2F3364%3Frss%3D1</link>
            <description>Discussion: First, &amp;gt;6000 possible siRNAs were designed. Successive filtration followed where a novel method for siRNA scoring filtration layers was implemented. This method excluded siRNAs below the 90% experimental inhibition mapped scores using the intersection of 12 different scoring algorithms. Further filtration of siRNAs is done by eliminating those with off-targets in the human genome and those with undesirable properties and selecting siRNA targeting highly probable single-stranded regions. Finally, the optimal properties of the siRNA were ensured through selection of those targeting 100% conserved, biologically functional short motifs. Validation of a predicted active (sh114) and a predicted inactive (sh113) (that was filtered out in Stage 8) silencer of the NS1 gene showed sig...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5484114</comments>
            <pubDate>Tue, 06 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5484114</guid>        </item>
        <item>
            <title>An assessment of substitution scores for protein profile-profile comparison</title>
            <link>http://www.medworm.com/index.php?rid=5484113&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F24%2F3356%3Frss%3D1</link>
            <description>Motivation: Pairwise protein sequence alignments are generally evaluated using scores defined as the sum of substitution scores for aligning amino acids to one another, and gap scores for aligning runs of amino acids in one sequence to null characters inserted into the other. Protein profiles may be abstracted from multiple alignments of protein sequences, and substitution and gap scores have been generalized to the alignment of such profiles either to single sequences or to other profiles. Although there is widespread agreement on the general form substitution scores should take for profile-sequence alignment, little consensus has been reached on how best to construct profile&amp;ndash;profile substitution scores, and a large number of these scoring systems have been proposed. Here, we assess...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5484113</comments>
            <pubDate>Tue, 06 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5484113</guid>        </item>
        <item>
            <title>KABOOM! A new suffix array based algorithm for clustering expression data</title>
            <link>http://www.medworm.com/index.php?rid=5484112&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F24%2F3348%3Frss%3D1</link>
            <description>Motivation: Second-generation sequencing technology has reinvigorated research using expression data, and clustering such data remains a significant challenge, with much larger datasets and with different error profiles. Algorithms that rely on all-versus-all comparison of sequences are not practical for large datasets.
Results: We introduce a new filter for string similarity which has the potential to eliminate the need for all-versus-all comparison in clustering of expression data and other similar tasks. Our filter is based on multiple long exact matches between the two strings, with the additional constraint that these matches must be sufficiently far apart. We give details of its efficient implementation using modified suffix arrays. We demonstrate its efficiency by presenting our new...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5484112</comments>
            <pubDate>Tue, 06 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5484112</guid>        </item>
        <item>
            <title>MetaRank: a rank conversion scheme for comparative analysis of microbial community compositions</title>
            <link>http://www.medworm.com/index.php?rid=5484111&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F24%2F3341%3Frss%3D1</link>
            <description>Motivation: Metagenomics involves sampling and studying the genetic materials in microbial communities. Several statistical methods have been proposed for comparative analysis of microbial community compositions. Most of the methods are based on the estimated abundances of taxonomic units or functional groups from metagenomic samples. However, such estimated abundances might deviate from the true abundances in habitats due to sampling biases and other systematic artifacts in metagenomic data processing.
Results: We developed the MetaRank scheme to convert abundances into ranks. MetaRank employs a series of statistical hypothesis tests to compare abundances within a microbial community and determine their ranks. We applied MetaRank to synthetic samples and real metagenomes. The results conf...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5484111</comments>
            <pubDate>Tue, 06 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5484111</guid>        </item>
        <item>
            <title>Pyicos: a versatile toolkit for the analysis of high-throughput sequencing data</title>
            <link>http://www.medworm.com/index.php?rid=5484110&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F24%2F3333%3Frss%3D1</link>
            <description>We describe Pyicos, a powerful toolkit for the analysis of mapped reads from diverse HTS experiments: ChIP-Seq, either punctuated or broad signals, CLIP-Seq and RNA-Seq. We prove the effectiveness of Pyicos to select for significant signals and show that its accuracy is comparable and sometimes superior to that of methods specifically designed for each particular type of experiment. Pyicos facilitates the analysis of a variety of HTS datatypes through its flexibility and memory efficiency, providing a useful framework for data integration into models of regulatory genomics.
Availability: Open-source software, with tutorials and protocol files, is available at http://regulatorygenomics.upf.edu/pyicos or as a Galaxy server at http://regulatorygenomics.upf.edu/galaxy
Contact: eduardo.eyras@up...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5484110</comments>
            <pubDate>Tue, 06 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5484110</guid>        </item>
        <item>
            <title>The rise and fall of supervised machine learning techniques</title>
            <link>http://www.medworm.com/index.php?rid=5484109&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F24%2F3331%3Frss%3D1</link>
            <description>(Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5484109</comments>
            <pubDate>Tue, 06 Dec 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5484109</guid>        </item>
        <item>
            <title>miREnvironment Database: providing a bridge for microRNAs, environmental factors and phenotypes</title>
            <link>http://www.medworm.com/index.php?rid=5448078&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F23%2F3329%3Frss%3D1</link>
            <description>In this study, we constructed the miREnvironment database, which contains a comprehensive collection and curation of experimentally supported interactions among miRNAs, environmental factors and phenotypes. The names of miRNAs, phenotypes, environmental factors, conditions of environmental factors, samples, species, evidence and references were further annotated. miREnvironment represents a biomedical resource for researches on miRNAs, environmental factors and diseases.
Availability: http://cmbi.bjmu.edu.cn/miren.
Contact: cuiqinghua@hsc.pku.edu.cn (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5448078</comments>
            <pubDate>Wed, 23 Nov 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5448078</guid>        </item>
        <item>
            <title>BioTextQuest: a web-based biomedical text mining suite for concept discovery</title>
            <link>http://www.medworm.com/index.php?rid=5448077&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F23%2F3327%3Frss%3D1</link>
            <description>Summary: BioTextQuest combines automated discovery of significant terms in article clusters with structured knowledge annotation, via Named Entity Recognition services, offering interactive user-friendly visualization. A tag-cloud-based illustration of terms labeling each document cluster are semantically annotated according to the biological entity, and a list of document titles enable users to simultaneously compare terms and documents of each cluster, facilitating concept association and hypothesis generation. BioTextQuest allows customization of analysis parameters, e.g. clustering/stemming algorithms, exclusion of documents/significant terms, to better match the biological question addressed.
Availability: http://biotextquest.biol.ucy.ac.cy
Contact: vprobon@ucy.ac.cy; iliopj@med.uoc.g...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5448077</comments>
            <pubDate>Wed, 23 Nov 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5448077</guid>        </item>
        <item>
            <title>PRINCIPLE: a tool for associating genes with diseases via network propagation</title>
            <link>http://www.medworm.com/index.php?rid=5448076&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F23%2F3325%3Frss%3D1</link>
            <description>Summary: PRINCIPLE is a Java application implemented as a Cytoscape plug-in, based on a previously published algorithm, PRINCE. Given a query disease, it prioritizes disease-related genes based on their closeness in a protein&amp;ndash;protein interaction network to genes causing phenotypically similar disorders to the query disease.
Availability: Implemented in Java, PRINCIPLE runs over Cytoscape 2.7 or newer versions. Binaries, default input files and documentation are freely available at http://www.cs.tau.ac.il/~bnet/software/PrincePlugin/.
Contact:roded@tau.ac.il; assafgot@tau.ac.il (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5448076</comments>
            <pubDate>Wed, 23 Nov 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5448076</guid>        </item>
        <item>
            <title>The Infobiotics Workbench: an integrated in silico modelling platform for Systems and Synthetic Biology</title>
            <link>http://www.medworm.com/index.php?rid=5448075&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F23%2F3323%3Frss%3D1</link>
            <description>Summary: The Infobiotics Workbench is an integrated software suite incorporating model specification, simulation, parameter optimization and model checking for Systems and Synthetic Biology. A modular model specification allows for straightforward creation of large-scale models containing many compartments and reactions. Models are simulated either using stochastic simulation or numerical integration, and visualized in time and space. Model parameters and structure can be optimized with evolutionary algorithms, and model properties calculated using probabilistic model checking.
Availability: Source code and binaries for Linux, Mac and Windows are available at http://www.infobiotics.org/infobiotics-workbench/; released under the GNU General Public License (GPL) version 3.
Contact: Natalio.K...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5448075</comments>
            <pubDate>Wed, 23 Nov 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5448075</guid>        </item>
        <item>
            <title>MyBioNet: interactively visualize, edit and merge biological networks on the Web</title>
            <link>http://www.medworm.com/index.php?rid=5448074&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F23%2F3321%3Frss%3D1</link>
            <description>Summary: MyBioNet is a web-based application for biological network analysis, which provides user-friendly web interfaces to visualize, edit and merge biological networks. In addition, MyBioNet integrated KEGG metabolic network data from 1366 organisms and allows users to search and navigate interesting networks.
Availability and Implementation: All KEGG metabolic network data are organized and stored in the MySQL database. MyBioNet is implemented in Flex/Actionscript and PHP languages and deployed on an Apache web server. MyBioNet is accessible through all the Flash-embedded browsers at http://bis.zju.edu.cn/mybionet/.
Contact:mchen@zju.edu.cn (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5448074</comments>
            <pubDate>Wed, 23 Nov 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5448074</guid>        </item>
        <item>
            <title>FlyExpress: visual mining of spatiotemporal patterns for genes and publications in Drosophila embryogenesis</title>
            <link>http://www.medworm.com/index.php?rid=5448073&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F23%2F3319%3Frss%3D1</link>
            <description>Summary: Images containing spatial expression patterns illuminate the roles of different genes during embryogenesis. In order to generate initial clues to regulatory interactions, biologists frequently need to know the set of genes expressed at the same time at specific locations in a developing embryo, as well as related research publications. However, text-based mining of image annotations and research articles cannot produce all relevant results, because the primary data are images that exist as graphical objects. We have developed a unique knowledge base (FlyExpress) to facilitate visual mining of images from Drosophila melanogaster embryogenesis. By clicking on specific locations in pictures of fly embryos from different stages of development and different visual projections, users ca...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5448073</comments>
            <pubDate>Wed, 23 Nov 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5448073</guid>        </item>
        <item>
            <title>ProfileChaser: searching microarray repositories based on genome-wide patterns of differential expression</title>
            <link>http://www.medworm.com/index.php?rid=5448072&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F23%2F3317%3Frss%3D1</link>
            <description>Summary: We introduce ProfileChaser, a web server that allows for querying the Gene Expression Omnibus based on genome-wide patterns of differential expression. Using a novel, content-based approach, ProfileChaser retrieves expression profiles that match the differentially regulated transcriptional programs in a user-supplied experiment. This analysis identifies statistical links to similar expression experiments from the vast array of publicly available data on diseases, drugs, phenotypes and other experimental conditions.
Availability: http://profilechaser.stanford.edu
Contact: abutte@stanford.edu
Supplementary Information: Supplementary data are available at Bioinformatics online. (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5448072</comments>
            <pubDate>Wed, 23 Nov 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5448072</guid>        </item>
        <item>
            <title>Automatic generation of protein structure cartoons with Pro-origami</title>
            <link>http://www.medworm.com/index.php?rid=5448071&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F23%2F3315%3Frss%3D1</link>
            <description>Summary: Protein topology diagrams are 2D representations of protein structure that are particularly useful in understanding and analysing complex protein folds. Generating such diagrams presents a major problem in graph drawing, with automatic approaches often resulting in errors or uninterpretable results. Here we apply a breakthrough in diagram layout to protein topology cartoons, providing clear, accurate, interactive and editable diagrams, which are also an interface to a structural search method.
Availability: Pro-origami is available via a web server at http://munk.csse.unimelb.edu.au/pro-origami
Contact: a.stivala@pgrad.unimelb.edu.au; pjs@csse.unimelb.edu.au (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5448071</comments>
            <pubDate>Wed, 23 Nov 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5448071</guid>        </item>
        <item>
            <title>CAMBerVis: visualization software to support comparative analysis of multiple bacterial strains</title>
            <link>http://www.medworm.com/index.php?rid=5448070&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F23%2F3313%3Frss%3D1</link>
            <description>Motivation: A number of inconsistencies in genome annotations are documented among bacterial strains. Visualization of the differences may help biologists to make correct decisions in spurious cases.
Results: We have developed a visualization tool, CAMBerVis, to support comparative analysis of multiple bacterial strains. The software manages simultaneous visualization of multiple bacterial genomes, enabling visual analysis focused on genome structure annotations.
Availability: The CAMBerVis software is freely available at the project website: http://bioputer.mimuw.edu.pl/camber. Input datasets for Mycobacterium tuberculosis and Staphylocacus aureus are integrated with the software as examples.
Contact: m.wozniak@mimuw.edu.pl
Supplementary Information:Supplementary data are available at Bio...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5448070</comments>
            <pubDate>Wed, 23 Nov 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5448070</guid>        </item>
        <item>
            <title>Extraction of data deposition statements from the literature: a method for automatically tracking research results</title>
            <link>http://www.medworm.com/index.php?rid=5448069&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F23%2F3306%3Frss%3D1</link>
            <description>Motivation: Research in the biomedical domain can have a major impact through open sharing of the data produced. For this reason, it is important to be able to identify instances of data production and deposition for potential re-use. Herein, we report on the automatic identification of data deposition statements in research articles.
Results: We apply machine learning algorithms to sentences extracted from full-text articles in PubMed Central in order to automatically determine whether a given article contains a data deposition statement, and retrieve the specific statements. With an Support Vector Machine classifier using conditional random field determined deposition features, articles containing deposition statements are correctly identified with 81% F-measure. An error analysis shows ...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5448069</comments>
            <pubDate>Wed, 23 Nov 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5448069</guid>        </item>
        <item>
            <title>Gathering insights on disease etiology from gene expression profiles of healthy tissues</title>
            <link>http://www.medworm.com/index.php?rid=5448068&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F23%2F3300%3Frss%3D1</link>
            <description>Motivation: Gene expression profiles have been widely used to study disease states. It may be possible, however, to gather insights into human diseases by comparing gene expression profiles of healthy organs with different disease incidence or severity. We tested this hypothesis and developed an approach to identify candidate genes associated with disease development by focusing on cancer incidence since it varies greatly across human organs.
Results: We normalized organ-specific cancer incidence by organ weight and found that reproductive organs tend to have a higher mass-normalized cancer incidence, which could be due to evolutionary trade-offs. Next, we performed a genome-wide scan to identify genes whose expression across healthy organs correlates with organ-specific cancer incidence. ...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5448068</comments>
            <pubDate>Wed, 23 Nov 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5448068</guid>        </item>
        <item>
            <title>Computational network analysis of the anatomical and genetic organizations in the mouse brain</title>
            <link>http://www.medworm.com/index.php?rid=5448067&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F23%2F3293%3Frss%3D1</link>
            <description>Motivation: The mammalian central nervous system (CNS) generates high-level behavior and cognitive functions. Elucidating the anatomical and genetic organizations in the CNS is a key step toward understanding the functional brain circuitry. The CNS contains an enormous number of cell types, each with unique gene expression patterns. Therefore, it is of central importance to capture the spatial expression patterns in the brain. Currently, genome-wide atlas of spatial expression patterns in the mouse brain has been made available, and the data are in the form of aligned 3D data arrays. The sheer volume and complexity of these data pose significant challenges for efficient computational analysis.
Results: We employ data reduction and network modeling techniques to explore the anatomical and g...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5448067</comments>
            <pubDate>Wed, 23 Nov 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5448067</guid>        </item>
        <item>
            <title>Protein stability: a single recorded mutation aids in predicting the effects of other mutations in the same amino acid site</title>
            <link>http://www.medworm.com/index.php?rid=5448066&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F23%2F3286%3Frss%3D1</link>
            <description>Motivation: Accurate prediction of protein stability is important for understanding the molecular underpinnings of diseases and for the design of new proteins. We introduce a novel approach for the prediction of changes in protein stability that arise from a single-site amino acid substitution; the approach uses available data on mutations occurring in the same position and in other positions. Our algorithm, named Pro-Maya (Protein Mutant stAbilitY Analyzer), combines a collaborative filtering baseline model, Random Forests regression and a diverse set of features. Pro-Maya predicts the stability free energy difference of mutant versus wild type, denoted as G.
Results: We evaluated our algorithm extensively using cross-validation on two previously utilized datasets of single amino acid mut...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5448066</comments>
            <pubDate>Wed, 23 Nov 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5448066</guid>        </item>
        <item>
            <title>MDpocket: open-source cavity detection and characterization on molecular dynamics trajectories</title>
            <link>http://www.medworm.com/index.php?rid=5448065&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F23%2F3276%3Frss%3D1</link>
            <description>This article describes a new method, called MDpocket, providing a fast, free and open-source tool for tracking small molecule binding sites and gas migration pathways on molecular dynamics (MDs) trajectories or other conformational ensembles. MDpocket is based on the fpocket cavity detection algorithm and a valuable contribution to existing analysis tools. The capabilities of MDpocket are illustrated for three relevant cases: (i) the detection of transient subpockets using an ensemble of crystal structures of HSP90; (ii) the detection of known xenon binding sites and migration pathways in myoglobin; and (iii) the identification of suitable pockets for molecular docking in P38 Map kinase.
Availability: MDpocket is free and open-source software and can be downloaded at http://fpocket.sourcef...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5448065</comments>
            <pubDate>Wed, 23 Nov 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5448065</guid>        </item>
        <item>
            <title>Pico-inplace-inversions between human and chimpanzee</title>
            <link>http://www.medworm.com/index.php?rid=5448064&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F23%2F3266%3Frss%3D1</link>
            <description>We report that the quantity of inplace-inversions between human and chimpanzee is substantially greater than what had previously been discovered. We also present the software tool PicoInversionMiner to detect pico-inplace-inversions between closely related species.
Availability: Software tools, scripts and result data are available at http://faculty.cs.niu.edu/~hou/PicoInversion.html.
Contact: mhou@cs.niu.edu (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5448064</comments>
            <pubDate>Wed, 23 Nov 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5448064</guid>        </item>
        <item>
            <title>Fast scaffolding with small independent mixed integer programs</title>
            <link>http://www.medworm.com/index.php?rid=5448063&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F23%2F3259%3Frss%3D1</link>
            <description>We present MIP Scaffolder that divides the scaffolding problem into smaller subproblems and solves these with mixed integer programming. The scaffolding problem can be represented as a graph and the biconnected components of this graph can be solved independently. We present a technique for restricting the size of these subproblems so that they can be solved accurately with mixed integer programming. We compare MIP Scaffolder to two state of the art methods, SOPRA and SSPACE. MIP Scaffolder is fast and produces better or as good scaffolds as its competitors on large genomes.
Availability: The source code of MIP Scaffolder is freely available at http://www.cs.helsinki.fi/u/lmsalmel/mip-scaffolder/.
Contact: leena.salmela@cs.helsinki.fi (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5448063</comments>
            <pubDate>Wed, 23 Nov 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5448063</guid>        </item>
        <item>
            <title>FASTSP: linear time calculation of alignment accuracy</title>
            <link>http://www.medworm.com/index.php?rid=5448062&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F23%2F3250%3Frss%3D1</link>
            <description>Motivation: Multiple sequence alignment is a basic part of much biological research, including phylogeny estimation and protein structure and function prediction. Different alignments on the same set of unaligned sequences are often compared, sometimes in order to assess the accuracy of alignment methods or to infer a consensus alignment from a set of estimated alignments.
Three of the standard techniques for comparing alignments, Developer, Modeler and Total Column (TC) scores can be derived through calculations of the set of homologies that the alignments share. However, the brute-force technique for calculating this set is quadratic in the input size. The remaining standard technique, Cline Shift Score, inherently requires quadratic time.
Results: In this article, we prove that each of ...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5448062</comments>
            <pubDate>Wed, 23 Nov 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5448062</guid>        </item>
        <item>
            <title>Sparse distance-based learning for simultaneous multiclass classification and feature selection of metagenomic data</title>
            <link>http://www.medworm.com/index.php?rid=5448061&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F23%2F3242%3Frss%3D1</link>
            <description>This article is the first to address simultaneous multifeature selection and class prediction with metagenomic count data.
Availability: The MATLAB toolbox is freely available online at http://metadistance.igs.umaryland.edu/.
Contact: zliu@umm.edu
Supplementary Information: Supplementary data are available at Bioinformatics online. (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5448061</comments>
            <pubDate>Wed, 23 Nov 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5448061</guid>        </item>
        <item>
            <title>Sequential Monte Carlo multiple testing</title>
            <link>http://www.medworm.com/index.php?rid=5448060&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F23%2F3235%3Frss%3D1</link>
            <description>Motivation: In molecular biology, as in many other scientific fields, the scale of analyses is ever increasing. Often, complex Monte Carlo simulation is required, sometimes within a large-scale multiple testing setting. The resulting computational costs may be prohibitively high.
Results: We here present MCFDR, a simple, novel algorithm for false discovery rate (FDR) modulated sequential Monte Carlo (MC) multiple hypothesis testing. The algorithm iterates between adding MC samples across tests and calculating intermediate FDR values for the collection of tests. MC sampling is stopped either by sequential MC or based on a threshold on FDR. An essential property of the algorithm is that it limits the total number of MC samples whatever the number of true null hypotheses. We show on both real...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5448060</comments>
            <pubDate>Wed, 23 Nov 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5448060</guid>        </item>
        <item>
            <title>SVseq: an approach for detecting exact breakpoints of deletions with low-coverage sequence data</title>
            <link>http://www.medworm.com/index.php?rid=5448059&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F23%2F3228%3Frss%3D1</link>
            <description>We present SVseq, an efficient two-stage approach, which combines the split reads mapping and discordant insert size analysis. The first stage is split reads mapping based on the Burrows&amp;ndash;Wheeler transform (BWT), which finds candidate deletions. Our split reads mapping method allows mismatches and small indels, thus deletions near other small variations can be discovered and reads with sequencing errors can be utilized. The second stage filters the false positives by analyzing discordant insert sizes. SVseq is more accurate than an alternative approach when applying on simulated data and empirical data, and is also much faster.
Availability: The program SVseq can be downloaded at http://www.engr.uconn.edu/~jiz08001/
Contact: jinzhang@engr.uconn.edu
Supplementary Information: Supplemen...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5448059</comments>
            <pubDate>Wed, 23 Nov 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5448059</guid>        </item>
        <item>
            <title>TIP: A probabilistic method for identifying transcription factor target genes from ChIP-seq binding profiles</title>
            <link>http://www.medworm.com/index.php?rid=5448058&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F23%2F3221%3Frss%3D1</link>
            <description>Conclusion: We show the advantages of TIP by comparing it to the &amp;lsquo;simple&amp;rsquo; approach on several representative datasets, using motif occurrence and relationship to knock-out experiments as metrics of validation. Moreover, we show that the probabilistic model is not as sensitive to various experimental parameters (including sequencing depth and peak-calling method) as the simple approach; in fact, the lesser dependence on sequencing depth potentially utilizes the result of a ChIP-seq experiment in a more &amp;lsquo;cost-effective&amp;rsquo; manner.
Contact: mark.gerstein@yale.edu
Supplementary Information: Supplementary data are available at Bioinformatics online. (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5448058</comments>
            <pubDate>Wed, 23 Nov 2011 05:00:00 +0100</pubDate>
            <guid isPermaLink="false">5448058</guid>        </item>
        <item>
            <title>DroPhEA: Drosophila phenotype enrichment analysis for insect functional genomics</title>
            <link>http://www.medworm.com/index.php?rid=5376938&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F22%2F3218%3Frss%3D1</link>
            <description>Summary: DroPhEA is a core module of a web application that facilitates research in insect functional genomics through enrichment analysis on mutant phenotypes of fruit fly (Drosophila melanogaster). The phenotypes investigated in the analyses can be predefined by FlyBase or customized by users. DroPhEA allows users to specify mutation or ortholog types, displays enriched term results in a hierarchical structure and supports analyses on gene sets of all insect species with a fully sequenced genome.
Availability: http://evol.nhri.org.tw/phenome/DroPhEA/
Contact: liaoby@nhri.org.tw
Supplementary Information: Supplementary data are available at Bioinformatics online. (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5376938</comments>
            <pubDate>Fri, 04 Nov 2011 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">5376938</guid>        </item>
        <item>
            <title>Kaviar: an accessible system for testing SNV novelty</title>
            <link>http://www.medworm.com/index.php?rid=5376937&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F22%2F3216%3Frss%3D1</link>
            <description>We present here Kaviar, a tool that greatly simplifies the assessment of novel variants. Kaviar includes: (i) an integrated and growing database of genomic variation from diverse sources, including over 55 million variants from personal genomes, family genomes, transcriptomes, SNV databases and population surveys; and (ii) software for querying the database efficiently.
Availability: Kaviar is programmed in Perl and offered free of charge as Open Source Software. Kaviar may be used online as a programmatic web service or downloaded for local use from http://db.systemsbiology.net/kaviar. The database is also provided.
Contact: gustavo@systemsbiology.org
Supplementary Information: Supplementary data are available at Bioinformatics online. (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5376937</comments>
            <pubDate>Fri, 04 Nov 2011 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">5376937</guid>        </item>
        <item>
            <title>Supporting tool suite for production proteomics</title>
            <link>http://www.medworm.com/index.php?rid=5376936&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F22%2F3214%3Frss%3D1</link>
            <description>We present the Backup Utility Service tool for automated instrument file backup and the ScanSifter tool for data conversion. We also describe a queuing system to coordinate identification pipelines and the File Collector tool for batch copying analytical results. These tools are individually useful but collectively reinforce each other. They are particularly valuable for proteomics core facilities or research institutions that need to manage multiple mass spectrometers. With minor changes, they could support other types of biomolecular resource facilities.
Availability and Implementation: Source code and executable versions are available under Apache 2.0 License at http://www.vicc.org/jimayersinstitute/data/
Contact: daniel.liebler@vanderbilt.edu (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5376936</comments>
            <pubDate>Fri, 04 Nov 2011 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">5376936</guid>        </item>
        <item>
            <title>Visual DSD: a design and analysis tool for DNA strand displacement systems</title>
            <link>http://www.medworm.com/index.php?rid=5376935&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F22%2F3211%3Frss%3D1</link>
            <description>Summary: The Visual DSD (DNA Strand Displacement) tool allows rapid prototyping and analysis of computational devices implemented using DNA strand displacement, in a convenient web-based graphical interface. It is an implementation of the DSD programming language and compiler described by Lakin et al. (2011) with additional features such as support for polymers of unbounded length. It also supports stochastic and deterministic simulation, construction of continuous-time Markov chains and various export formats which allow models to be analysed using third-party tools.
Availability: Visual DSD is available as a web-based Silverlight application for most major browsers on Windows and Mac OS X at http://research.microsoft.com/dna. It can be installed locally for offline use. Command-line vers...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5376935</comments>
            <pubDate>Fri, 04 Nov 2011 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">5376935</guid>        </item>
        <item>
            <title>RNA-Seq analysis in MeV</title>
            <link>http://www.medworm.com/index.php?rid=5376934&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F22%2F3209%3Frss%3D1</link>
            <description>Summary: RNA-Seq is an exciting methodology that leverages the power of high-throughput sequencing to measure RNA transcript counts at an unprecedented accuracy. However, the data generated from this process are extremely large and biologist-friendly tools with which to analyze it are sorely lacking. MultiExperiment Viewer (MeV) is a Java-based desktop application that allows advanced analysis of gene expression data through an intuitive graphical user interface. Here, we report a significant enhancement to MeV that allows analysis of RNA-Seq data with these familiar, powerful tools. We also report the addition to MeV of several RNA-Seq-specific functions, addressing the differences in analysis requirements between this data type and traditional gene expression data. These tools include au...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5376934</comments>
            <pubDate>Fri, 04 Nov 2011 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">5376934</guid>        </item>
        <item>
            <title>survcomp: an R/Bioconductor package for performance assessment and comparison of survival models</title>
            <link>http://www.medworm.com/index.php?rid=5376933&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F22%2F3206%3Frss%3D1</link>
            <description>Summary: The survcomp package provides functions to assess and statistically compare the performance of survival/risk prediction models. It implements state-of-the-art statistics to (i) measure the performance of risk prediction models; (ii) combine these statistical estimates from multiple datasets using a meta-analytical framework; and (iii) statistically compare the performance of competitive models.
Availability: The R/Bioconductor package survcomp is provided open source under the Artistic-2.0 License with a user manual containing installation, operating instructions and use case scenarios on real datasets. survcomp requires R version 2.13.0 or higher. http://bioconductor.org/packages/release/bioc/html/survcomp.html
Contact: bhaibeka@jimmy.harvard.edu; mschroed@jimmy.harvard.edu
Suppl...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5376933</comments>
            <pubDate>Fri, 04 Nov 2011 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">5376933</guid>        </item>
        <item>
            <title>inSilicoDb: an R/Bioconductor package for accessing human Affymetrix expert-curated datasets from GEO</title>
            <link>http://www.medworm.com/index.php?rid=5376932&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F22%2F3204%3Frss%3D1</link>
            <description>Microarray technology has become an integral part of biomedical research and increasing amounts of datasets become available through public repositories. However, re-use of these datasets is severely hindered by unstructured, missing or incorrect biological samples information; as well as the wide variety of preprocessing methods in use. The inSilicoDb R/Bioconductor package is a command-line front-end to the InSilico DB, a web-based database currently containing 86 104 expert-curated human Affymetrix expression profiles compiled from 1937 GEO repository series. The use of this package builds on the Bioconductor project's focus on reproducibility by enabling a clear workflow in which not only analysis, but also the retrieval of verified data is supported.
Availability: inSilicoDb is availa...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5376932</comments>
            <pubDate>Fri, 04 Nov 2011 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">5376932</guid>        </item>
        <item>
            <title>A non-biased framework for the annotation and classification of the non-miRNA small RNA transcriptome</title>
            <link>http://www.medworm.com/index.php?rid=5376931&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F22%2F3202%3Frss%3D1</link>
            <description>Motivation: Recent progress in high-throughput sequencing technologies has largely contributed to reveal a highly complex landscape of small non-coding RNAs (sRNAs), including novel non-canonical sRNAs derived from long non-coding RNA, repeated elements, transcription start sites and splicing site regions among others. The published frameworks for sRNA data analysis are focused on miRNA detection and prediction, ignoring further information in the dataset. As a consequence, tools for the identification and classification of the sRNAs not belonging to miRNA family are currently lacking.
Results: Here, we present, SeqCluster, an extension of the currently available SeqBuster tool to identify and analyze at different levels the sRNAs not annotated or predicted as miRNAs. This new module deals...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5376931</comments>
            <pubDate>Fri, 04 Nov 2011 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">5376931</guid>        </item>
        <item>
            <title>Knime4Bio: a set of custom nodes for the interpretation of next-generation sequencing data with KNIME</title>
            <link>http://www.medworm.com/index.php?rid=5376930&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F22%2F3200%3Frss%3D1</link>
            <description>Summary: Analysing large amounts of data generated by next-generation sequencing (NGS) technologies is difficult for researchers or clinicians without computational skills. They are often compelled to delegate this task to computer biologists working with command line utilities. The availability of easy-to-use tools will become essential with the generalization of NGS in research and diagnosis. It will enable investigators to handle much more of the analysis. Here, we describe Knime4Bio, a set of custom nodes for the KNIME (The Konstanz Information Miner) interactive graphical workbench, for the interpretation of large biological datasets. We demonstrate that this tool can be utilized to quickly retrieve previously published scientific findings.
Availability: http://code.google.com/p/knime...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5376930</comments>
            <pubDate>Fri, 04 Nov 2011 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">5376930</guid>        </item>
        <item>
            <title>PIDO: the primary immunodeficiency disease ontology</title>
            <link>http://www.medworm.com/index.php?rid=5376929&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F22%2F3193%3Frss%3D1</link>
            <description>We present PIDO, the primary immunodeficiency disease ontology. PIDO characterizes PIDs in terms of the phenotypes commonly observed by clinicians during a diagnosis process. Phenotype terms in PIDO are formally defined using complex definitions based on qualities, functions, processes and structures. We provide mappings to biomedical reference ontologies to ensure interoperability with ontologies in other domains. Based on PIDO, we developed the PIDFinder, an ontology-driven software prototype that can facilitate clinical decision support. PIDO connects immunological knowledge across resources within a common framework and thereby enables translational research and the development of medical applications for the domain of immunology and primary immunodeficiency diseases.
Availability: The...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5376929</comments>
            <pubDate>Fri, 04 Nov 2011 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">5376929</guid>        </item>
        <item>
            <title>ISPyB: an information management system for synchrotron macromolecular crystallography</title>
            <link>http://www.medworm.com/index.php?rid=5376928&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F22%2F3186%3Frss%3D1</link>
            <description>Motivation: Individual research groups now analyze thousands of samples per year at synchrotron macromolecular crystallography (MX) resources. The efficient management of experimental data is thus essential if the best possible experiments are to be performed and the best possible data used in downstream processes in structure determination pipelines. Information System for Protein crystallography Beamlines (ISPyB), a Laboratory Information Management System (LIMS) with an underlying data model allowing for the integration of analyses down-stream of the data collection experiment was developed to facilitate such data management.
Results: ISPyB is now a multisite, generic LIMS for synchrotron-based MX experiments. Its initial functionality has been enhanced to include improved sample tracki...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5376928</comments>
            <pubDate>Fri, 04 Nov 2011 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">5376928</guid>        </item>
        <item>
            <title>Weakly supervised learning of information structure of scientific abstracts--is it accurate enough to benefit real-world tasks in biomedicine?</title>
            <link>http://www.medworm.com/index.php?rid=5376927&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F22%2F3179%3Frss%3D1</link>
            <description>Motivation: Many practical tasks in biomedicine require accessing specific types of information in scientific literature; e.g. information about the methods, results or conclusions of the study in question. Several approaches have been developed to identify such information in scientific journal articles. The best of these have yielded promising results and proved useful for biomedical text mining tasks. However, relying on fully supervised machine learning (ml) and a large body of annotated data, existing approaches are expensive to develop and port to different tasks. A potential solution to this problem is to employ weakly supervised learning instead. In this article, we investigate a weakly supervised approach to identifying information structure according to a scheme called Argumentat...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5376927</comments>
            <pubDate>Fri, 04 Nov 2011 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">5376927</guid>        </item>
        <item>
            <title>An efficient network querying method based on conditional random fields</title>
            <link>http://www.medworm.com/index.php?rid=5376926&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F22%2F3173%3Frss%3D1</link>
            <description>Motivation: A large amount of biomolecular network data for multiple species have been generated by high-throughput experimental techniques, including undirected and directed networks such as protein&amp;ndash;protein interaction networks, gene regulatory networks and metabolic networks. There are many conserved functionally similar modules and pathways among multiple biomolecular networks in different species; therefore, it is important to analyze the similarity between the biomolecular networks. Network querying approaches aim at efficiently discovering the similar subnetworks among different species. However, many existing methods only partially solve this problem.
Results: In this article, a novel approach for network querying problem based on conditional random fields (CRFs) model is pres...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5376926</comments>
            <pubDate>Fri, 04 Nov 2011 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">5376926</guid>        </item>
        <item>
            <title>Unsupervised detection of genes of influence in lung cancer using biological networks</title>
            <link>http://www.medworm.com/index.php?rid=5376925&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F22%2F3166%3Frss%3D1</link>
            <description>Conclusion: Our model is flexible, robust and identifies gene sets that are more consistent across cohorts than several other approaches. Additionally, our method can be applied on a per-patient basis not requiring large cohorts of patients to find genes of influence. Our approach is generally applicable to gene expression studies where the goal is to identify a small set of influential genes that may in turn explain the much larger set of genome-wide expression changes.
Availability: The code is available at http://morrislab.med.utoronto.ca/~anna/cannet.zip
Contact: anna.goldenberg@utoronto.ca
Supplementary Information: Supplementary data are available at Bioinformatics online. (Source: Bioinformatics)</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5376925</comments>
            <pubDate>Fri, 04 Nov 2011 04:00:00 +0100</pubDate>
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        <item>
            <title>Neural fate decisions mediated by trans-activation and cis-inhibition in Notch signaling</title>
            <link>http://www.medworm.com/index.php?rid=5376924&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F22%2F3158%3Frss%3D1</link>
            <description>Motivation: In the developing nervous system, the expression of proneural genes, i.e. Hes1, Neurogenin-2 (Ngn2) and Deltalike-1 (Dll1), oscillates in neural progenitors with a period of 2&amp;ndash;3 h, but is persistent in post-mitotic neurons. Unlike the synchronization of segmentation clocks, oscillations in neural progenitors are asynchronous between cells. It is known that Notch signaling, in which Notch in a cell can be activated by Dll1 in neighboring cells (trans-activation) and can also be inhibited by Dll1 within the same cell (cis-inhibition), is important for neural fate decisions. There have been extensive studies of trans-activation, but the operating mechanisms and potential implications of cis-inhibition are less clear and need to be further investigated.
Results: In this artic...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5376924</comments>
            <pubDate>Fri, 04 Nov 2011 04:00:00 +0100</pubDate>
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        <item>
            <title>TFRank: network-based prioritization of regulatory associations underlying transcriptional responses</title>
            <link>http://www.medworm.com/index.php?rid=5376923&amp;cid=s_31985_79_f&amp;fid=31985&amp;url=http%3A%2F%2Fbioinformatics.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2F27%2F22%2F3149%3Frss%3D1</link>
            <description>We present TFRank, a graph-based framework to prioritize regulatory players involved in transcriptional responses within the regulatory network of an organism, whereby every regulatory path containing genes of interest is explored and incorporated into the analysis. TFRank selected important regulators of yeast adaptation to stress induced by quinine and acetic acid, which were missed by a direct effect approach. Notably, they reportedly confer resistance toward the chemicals. In a preliminary study in human, TFRank unveiled regulators involved in breast tumor growth and metastasis when applied to genes whose expression signatures correlated with short interval to metastasis.
Availability: Prototype at http://kdbio.inesc-id.pt/software/tfrank/.
Contact: jpg@kdbio.inesc-id.pt; sara.madeira@...</description>
            <author>Bioinformatics</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5376923</comments>
            <pubDate>Fri, 04 Nov 2011 04:00:00 +0100</pubDate>
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