References of "Bioinformatics"
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See detailEnrichNet: network-based gene set enrichment analysis
Glaab, Enrico UL; Baudot, A.; Krasnogor, N. et al

in Bioinformatics (2012), 28(18), 451-457

Assessing functional associations between an experimentally derived gene or protein set of interest and a database of known gene/protein sets is a common task in the analysis of large-scale functional ... [more ▼]

Assessing functional associations between an experimentally derived gene or protein set of interest and a database of known gene/protein sets is a common task in the analysis of large-scale functional genomics data. For this purpose, a frequently used approach is to apply an over-representation-based enrichment analysis. However, this approach has four drawbacks: (i) it can only score functional associations of overlapping gene/proteins sets; (ii) it disregards genes with missing annotations; (iii) it does not take into account the network structure of physical interactions between the gene/protein sets of interest and (iv) tissue-specific gene/protein set associations cannot be recognized. RESULTS: To address these limitations, we introduce an integrative analysis approach and web-application called EnrichNet. It combines a novel graph-based statistic with an interactive sub-network visualization to accomplish two complementary goals: improving the prioritization of putative functional gene/protein set associations by exploiting information from molecular interaction networks and tissue-specific gene expression data and enabling a direct biological interpretation of the results. By using the approach to analyse sets of genes with known involvement in human diseases, new pathway associations are identified, reflecting a dense sub-network of interactions between their corresponding proteins. [less ▲]

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See detailPathVar: analysis of gene and protein expression variance in cellular pathways using microarray data
Glaab, Enrico UL; Schneider, Reinhard UL

in Bioinformatics (2012)

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 ... [more ▼]

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 across different biological conditions. Apart from identifying new pathway deregulation patterns, the tool exploits these patterns by combining different machine learning methods to find clusters of similar samples and build sample classification models. [less ▲]

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See detailAutomated workflows for accurate mass-based putative metabolite identification in LC/MS-derived metabolomic datasets.
Brown, Marie; Wedge, David C.; Goodacre, Royston et al

in Bioinformatics (2011), 27(8), 1108-12

MOTIVATION: The study of metabolites (metabolomics) is increasingly being applied to investigate microbial, plant, environmental and mammalian systems. One of the limiting factors is that of chemically ... [more ▼]

MOTIVATION: The study of metabolites (metabolomics) is increasingly being applied to investigate microbial, plant, environmental and mammalian systems. One of the limiting factors is that of chemically identifying metabolites from mass spectrometric signals present in complex datasets. RESULTS: Three workflows have been developed to allow for the rapid, automated and high-throughput annotation and putative metabolite identification of electrospray LC-MS-derived metabolomic datasets. The collection of workflows are defined as PUTMEDID_LCMS and perform feature annotation, matching of accurate m/z to the accurate mass of neutral molecules and associated molecular formula and matching of the molecular formulae to a reference file of metabolites. The software is independent of the instrument and data pre-processing applied. The number of false positives is reduced by eliminating the inaccurate matching of many artifact, isotope, multiply charged and complex adduct peaks through complex interrogation of experimental data. AVAILABILITY: The workflows, standard operating procedure and further information are publicly available at http://www.mcisb.org/resources/putmedid.html. CONTACT: warwick.dunn@manchester.ac.uk. [less ▲]

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See detailTopoGSA: network topological gene set analysis
Glaab, Enrico UL; Baudot, Anais; Krasnogor, Natalio et al

in Bioinformatics (2010), 26(9), 1271-1272

TopoGSA (Topology-based Gene Set Analysis) is a web-application dedicated to the computation and visualization of network topological properties for gene and protein sets in molecular interaction networks ... [more ▼]

TopoGSA (Topology-based Gene Set Analysis) is a web-application dedicated to the computation and visualization of network topological properties for gene and protein sets in molecular interaction networks. Different topological characteristics, such as the centrality of nodes in the network or their tendency to form clusters, can be computed and compared with those of known cellular pathways and processes. [less ▲]

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See detailjClust: a clustering and visualization toolbox
Pavlopoulos, Georgios A.; Moschopoulos, Charalampos N.; Hooper, Sean D. et al

in Bioinformatics (2009), 25(15), 1994-1996

jClust is a user-friendly application which provides access to a set of widely used clustering and clique finding algorithms. The toolbox allows a range of filtering procedures to be applied and is ... [more ▼]

jClust is a user-friendly application which provides access to a set of widely used clustering and clique finding algorithms. The toolbox allows a range of filtering procedures to be applied and is combined with an advanced implementation of the Medusa interactive visualization module. These implemented algorithms are k-Means, Affinity propagation, Bron-Kerbosch, MULIC, Restricted neighborhood search cluster algorithm, Markov clustering and Spectral clustering, while the supported filtering procedures are haircut, outside-inside, best neighbors and density control operations. The combination of a simple input. le format, a set of clustering and filtering algorithms linked together with the visualization tool provides a powerful tool for data analysis and information extraction. [less ▲]

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See detailMethyl side-chain dynamics prediction based on protein structure
Carbonell, P.; del Sol Mesa, Antonio UL

in Bioinformatics (2009), 25(19), 2552-8

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See detailOnTheFly: a tool for automated document-based text annotation, data linking and network generation
Pavlopoulos, Georgios A.; Pafilis, Evangelos; Kuhn, M. et al

in Bioinformatics (2009), 25(7), 977-978

OnTheFly is a web-based application that applies biological named entity recognition to enrich Microsoft Office, PDF and plain text documents. The input files are converted into the HTML format and then ... [more ▼]

OnTheFly is a web-based application that applies biological named entity recognition to enrich Microsoft Office, PDF and plain text documents. The input files are converted into the HTML format and then sent to the Reflect tagging server, which highlights biological entity names like genes, proteins and chemicals, and attaches to them JavaScript code to invoke a summary pop-up window. The window provides an overview of relevant information about the entity, such as a protein description, the domain composition, a link to the 3D structure and links to other relevant online resources. OnTheFly is also able to extract the bioentities mentioned in a set of files and to produce a graphical representation of the networks of the known and predicted associations of these entities by retrieving the information from the STITCH database. [less ▲]

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See detailMetaQuant: a tool for the automatic quantification of GC/MS-based metabolome data
Bunk, Boyke; Kucklick, Martin; Münch, Richard et al

in Bioinformatics (2006)

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See detailVirtual Footprint and PRODORIC: an integrative framework for regulon prediction in prokaryotes
Münch, Richard; Hiller, Karsten UL; Grote, Andreas et al

in Bioinformatics (2005)

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See detailA Gibbs sampler for identification of symmetrically structured, spaced DNA motifs with improved estimation of the signal length
Favorov, A.A.; Gelfand, M.S.; Gerasimova, A.V. et al

in Bioinformatics (2005), 21(10), 2240-2245

Motivation: Transcription regulatory protein factors often bind DNA as homo-dimers or hetero-dimers. Thus they recognize structured DNA motifs that are inverted or direct repeats or spaced motif pairs ... [more ▼]

Motivation: Transcription regulatory protein factors often bind DNA as homo-dimers or hetero-dimers. Thus they recognize structured DNA motifs that are inverted or direct repeats or spaced motif pairs. However, these motifs are often difficult to identify owing to their high divergence. The motif structure included explicitly into the motif recognition algorithm improves recognition efficiency for highly divergent motifs as well as estimation of motif geometric parameters. Result: We present a modification of the Gibbs sampling motif extraction algorithm, SeSiMCMC (Sequence Similarities by Markov Chain Monte Carlo), which finds structured motifs of these types, as well as non-structured motifs, in a set of unaligned DNA sequences. It employs improved estimators of motif and spacer lengths. The probability that a sequence does not contain any motif is accounted for in a rigorous Bayesian manner. We have applied the algorithm to a set of upstream regions of genes from two Escherichia coli regulons involved in respiration. We have demonstrated that accounting for a symmetric motif structure allows the algorithm to identify weak motifs more accurately. In the examples studied, ArcA binding sites were demonstrated to have the structure of a direct spaced repeat, whereas NarP binding sites exhibited the palindromic structure. Availability: The WWW interface of the program, its FreeBSD (4.0) and Windows 32 console executables are available at http://bioinform.genetika.ru/SeSiMCMC [less ▲]

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See detailComputational methods for the design of effective therapies against drug resistant HIV strains
Beerenwinkel, N.; Sing, T.; Lengauer, T. et al

in Bioinformatics (2005), 21(21), 3943-50

Summary: The development of drug resistance is a major obstacle to successful treatment of HIV infection. The extraordinary replication dynamics of HIV facilitates its escape from selective pressure ... [more ▼]

Summary: The development of drug resistance is a major obstacle to successful treatment of HIV infection. The extraordinary replication dynamics of HIV facilitates its escape from selective pressure exerted by the human immune system and by combination drug therapy. We have developed several computational methods whose combined use can support the design of optimal antiretroviral therapies based on viral genomic data. [less ▲]

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See detailLimited conformational space for early-stage protein folding simulation
Brylinski, M.; Jurkowski, Wiktor UL; Konieczny, L. et al

in Bioinformatics (2004), 20(2), 199-205

MOTIVATION: The problem of early-stage protein folding is critical for protein structure prediction. The model presented introduces a common definition of protein structures which may be treated as the ... [more ▼]

MOTIVATION: The problem of early-stage protein folding is critical for protein structure prediction. The model presented introduces a common definition of protein structures which may be treated as the possible in silico early-stage form of the polypeptide chain. Limitation of the conformational space to the ellipse path on the Ramachandran map was tested as a possible sub-space to represent the early-stage structure for simulation of protein folding. The proposed conformational sub-space was developed on the basis of the backbone conformation, with side-chain interactions excluded. RESULTS: The ellipse-path-limited conformation of BPTI was created using the criterion of shortest distance between Phi, Psi angles in native form of protein and the Phi, Psi angles belonging to the ellipse. No knots were observed in the structure created according to ellipse-path conformational sub-space. The energy minimization procedure applied to ellipse-path derived conformation directed structural changes toward the native form of the protein with SS-bonds system introduced to the procedure. AVAILABILITY: Program 'Ellipse' to create the ellipse-path derived structure available on request: myroterm@cyf-kr.edu.pl [less ▲]

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See detailINTERPRO
Apweiler, R.; Attwood, T. K.; Bairoch, A. et al

in Bioinformatics (2000)

InterPro is a new integrated documentation resource for protein families, domains and functional sites, developed as a means of rationalising the complementary efforts of the PROSITE, PRINTS, Pfam and ... [more ▼]

InterPro is a new integrated documentation resource for protein families, domains and functional sites, developed as a means of rationalising the complementary efforts of the PROSITE, PRINTS, Pfam and ProDom database projects. Merged annotations from PRINTS, PROSITE and Pfam form the InterPro core. Each combined InterPro entry includes functional descriptions and literature references, and links are made back to the relevant parent database(s), allowing users to see at a glance whether a particular family or domain has associated patterns, profiles, fingerprints, etc.. Merged and individual entries (i.e., those that have no counterpart in the companion resources) are assigned unique accession numbers. The first release of InterPro contains around 2,400 entries, representing families, domains, repeats and sites of post-translational modification (PTMs) encoded by 4,300 regular expressions, profiles, fingerprints and Hidden Markov Models (HMMs). Each InterPro entry lists all the matches against SWISS-PROT and TrEMBL (more than 370,000 hits in total). The database is accessible for text-based searches at http://www.ebi.ac.uk/ interpro/. [less ▲]

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