References of "Bioinformatics"
     in
Bookmark and Share    
Full Text
Peer Reviewed
See detailReconMap: An interactive visualisation of human metabolism
Noronha, Alberto UL; Danielsdóttir, Anna Dröfn; Jóhannsson, Freyr et al

in Bioinformatics (in press)

A genome-scale reconstruction of human metabolism, Recon 2, is available but no interface exists to interactively visualise its content integrated with omics data and simulation results. We manually drew ... [more ▼]

A genome-scale reconstruction of human metabolism, Recon 2, is available but no interface exists to interactively visualise its content integrated with omics data and simulation results. We manually drew a comprehensive map, ReconMap 2.0, that is consistent with the content of Recon 2. We present it within a web interface that allows content query, visualization of custom datasets and submission of feedback to manual curators. ReconMap can be accessed via http://vmh.uni.lu, with network export in a Systems Biology Graphical Notation compliant format. A Constraint-Based Reconstruction and Analysis (COBRA) Toolbox extension to interact with ReconMap is available via https://github.com/opencobra/cobratoolbox. [less ▲]

Detailed reference viewed: 211 (21 UL)
Full Text
Peer Reviewed
See detailThe new Protein Topology Graph Library web server
Schäfer, Tim; Bruneß, Daniel; Scheck, Andreas et al

in Bioinformatics (2016), 32(3), 474-6

Summary: We present a new, extended version of the Protein Topology Graph Library (PTGL) web server. The PTGL describes the protein topology on the super-secondary structure level. It allows to compute ... [more ▼]

Summary: We present a new, extended version of the Protein Topology Graph Library (PTGL) web server. The PTGL describes the protein topology on the super-secondary structure level. It allows to compute and visualize protein ligand graphs and search for protein structural motifs. The new server features additional information on ligand binding to secondary structure elements (SSEs), increased usability, and an application programming interface (API) to retrieve data, allowing for an automated analysis of protein topology. Availability: The PTGL server is freely available on the web at http://ptgl.uni-frankfurt.de. The website is implemented in PHP, JavaScript, PostgreSQL and Apache. It is supported by all major browsers. The VPLG software that was used to compute the protein ligand graphs and all other data in the database is available under the GNU public license 2.0 from http://vplg.sourceforge.net. [less ▲]

Detailed reference viewed: 233 (5 UL)
Full Text
Peer Reviewed
See detailFastMotif: Spectral Sequence Motif Discovery
Colombo, Nicolo UL; Vlassis, Nikos UL

in Bioinformatics (2015)

Motivation: Sequence discovery tools play a central role in several fields of computational biology. In the framework of Transcription Factor binding studies, most of the existing motif finding algorithms ... [more ▼]

Motivation: Sequence discovery tools play a central role in several fields of computational biology. In the framework of Transcription Factor binding studies, most of the existing motif finding algorithms are computationally demanding, and they may not be able to support the increasingly large datasets produced by modern high-throughput sequencing technologies. Results: We present FastMotif, a new motif discovery algorithm that is built on a recent machine learning technique referred to as Method of Moments. Based on spectral decompositions, our method is robust to model misspecifications and is not prone to locally optimal solutions. We obtain an algorithm that is extremely fast and designed for the analysis of big sequencing data. On HT-Selex data, FastMotif extracts motif profiles that match those computed by various state-of- the-art algorithms, but one order of magnitude faster. We provide a theoretical and numerical analysis of the algorithm’s robustness and discuss its sensitivity with respect to the free parameters. [less ▲]

Detailed reference viewed: 56 (8 UL)
Full Text
Peer Reviewed
See detailRepExplore: Addressing technical replicate variance in proteomics and metabolomics data analysis
Glaab, Enrico UL; Schneider, Reinhard UL

in Bioinformatics (2015), 31(13), 2235

High-throughput omics datasets often contain technical replicates, included to account for technical sources of noise in the measurement process. Although summarizing these replicate measurements by using ... [more ▼]

High-throughput omics datasets often contain technical replicates, included to account for technical sources of noise in the measurement process. Although summarizing these replicate measurements by using robust averages may help to reduce the influence of noise on downstream data analysis, the information on the variance across the replicate measurements is lost in the averaging process and therefore typically disregarded in subsequent statistical analyses. We introduce RepExplore, a web-service dedicated to exploit the information captured in the technical replicate variance to provide more reliable and informative differential expression and abundance statistics for omics datasets. The software builds on previously published statistical methods, which have been applied successfully to biomedical omics data but are difficult to use without prior experience in programming or scripting. RepExplore facilitates the analysis by providing a fully automated data processing and interactive ran- king tables, whisker plot, heat map and principal component analysis visualizations to interpret omics data and derived statistics. [less ▲]

Detailed reference viewed: 71 (11 UL)
Full Text
Peer Reviewed
See detailBioTextQuest+: a knowledge integration platform for literature mining and concept discovery
Papanikolaou, Nikolas; Pavlopoulos, Georgios A.; Pafilis, Evangelos et al

in Bioinformatics (2014)

The iterative process of finding relevant information in biomedical literature and performing bioinformatics analyses might result in an endless loop for an inexperienced user, considering the exponential ... [more ▼]

The iterative process of finding relevant information in biomedical literature and performing bioinformatics analyses might result in an endless loop for an inexperienced user, considering the exponential growth of scientific corpora and the plethora of tools designed to mine PubMed® and related biological databases. Herein, we describe BioTextQuest+, a web-based interactive knowledge exploration platform with significant advances to its predecessor (BioTextQuest), aiming to bridge processes such as bioentity recognition, functional annotation, document clustering and data integration towards literature mining and concept discovery. BioTextQuest+ enables PubMed and OMIM querying, retrieval of abstracts related to a targeted request and optimal detection of genes, proteins, molecular functions, pathways and biological processes within the retrieved documents. The front-end interface facilitates the browsing of document clustering per subject, the analysis of term co-occurrence, the generation of tag clouds containing highly represented terms per cluster and at-a-glance popup windows with information about relevant genes and proteins. Moreover, to support experimental research, BioTextQuest+ addresses integration of its primary functionality with biological repositories and software tools able to deliver further bioinformatics services. The Google-like interface extends beyond simple use by offering a range of advanced parameterization for expert users. We demonstrate the functionality of BioTextQuest+ through several exemplary research scenarios including author disambiguation, functional term enrichment, knowledge acquisition and concept discovery linking major human diseases, such as obesity and ageing. [less ▲]

Detailed reference viewed: 75 (7 UL)
Full Text
Peer Reviewed
See detailFASTGAPFILL: Efficient gap filling in metabolic networks
Thiele, Ines UL; Vlassis, Nikos UL; Fleming, Ronan MT UL

in Bioinformatics (2014), 30(17), 2529-2531

Motivation: Genome-scale metabolic reconstructions summarize current knowledge about a target organism in a structured manner and as such highlight missing information. Such gaps can be filled ... [more ▼]

Motivation: Genome-scale metabolic reconstructions summarize current knowledge about a target organism in a structured manner and as such highlight missing information. Such gaps can be filled algorithmically. Scalability limitations of available algorithms for gap filling hinder their application to compartmentalized reconstructions. Results:We present FASTGAPFILL, a computationally efficient,tractable extension to the COBRA toolbox that permits theidentification of candidate missing knowledge from a universal biochemical reaction database (e.g., KEGG) for a given (compart-mentalized) metabolic reconstruction. The stoichiometric consistency of the universal reaction database and of the metabolic reconstruction can be tested for permitting the computation of biologically more relevant solutions. We demonstrate the efficiency and scalability of fastGapFill on a range of metabolic reconstructions. [less ▲]

Detailed reference viewed: 97 (12 UL)
Full Text
Peer Reviewed
See detailNTFD - A stand-alone application for the non-targeted detection of stable isotope labeled compounds in GC/MS data.
Hiller, Karsten UL; Wegner, André UL; Weindl, Daniel UL et al

in Bioinformatics (2013), 29(9), 1226-8

SUMMARY: Most current stable isotope-based methodologies are targeted and focus only on the well-described aspects of metabolic networks. Here, we present NTFD (non-targeted tracer fate detection), a ... [more ▼]

SUMMARY: Most current stable isotope-based methodologies are targeted and focus only on the well-described aspects of metabolic networks. Here, we present NTFD (non-targeted tracer fate detection), a software for the non-targeted analysis of all detectable compounds derived from a stable isotope-labeled tracer present in a GC/MS dataset. In contrast to traditional metabolic flux analysis approaches, NTFD does not depend on any a priori knowledge or library information. To obtain dynamic information on metabolic pathway activity, NTFD determines mass isotopomer distributions for all detected and labeled compounds. These data provide information on relative fluxes in a metabolic network. The graphical user interface allows users to import GC/MS data in netCDF format and export all information into a tab-separated format. AVAILABILITY: NTFD is C++- and Qt4-based, and it is freely available under an open-source license. Pre-compiled packages for the installation on Debian- and Redhat-based Linux distributions, as well as Windows operating systems, along with example data, are provided for download at http://ntfd.mit.edu/. CONTACT: gregstep@mit.edu. [less ▲]

Detailed reference viewed: 89 (5 UL)
Full Text
Peer Reviewed
See detailIAnn: An event sharing platform for the life sciences
Jimenez, Rafael; Albar, Juan; Bhak, Jong et al

in Bioinformatics (2013)

Summary: We present iAnn, an open source community-driven platform for dissemination of life science events, such as courses, conferences and workshops. iAnn allows automatic visualisation and integration ... [more ▼]

Summary: We present iAnn, an open source community-driven platform for dissemination of life science events, such as courses, conferences and workshops. iAnn allows automatic visualisation and integration of customised event reports. A central repository lies at the core of the platform: curators add submitted events, and these are subsequently accessed via web services. Thus, once an iAnn widget is incorporated into a website, it permanently shows timely relevant information as if it were native to the remote site. At the same time, announcements submitted to the repository are automatically disseminated to all portals that query the system. To facilitate the visualization of announcements, iAnn provides powerful filtering options and views, integrated in Google Maps and Google Calendar. All iAnn widgets are freely available. [less ▲]

Detailed reference viewed: 16 (0 UL)
Full Text
Peer Reviewed
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 ▲]

Detailed reference viewed: 31 (9 UL)
Full Text
Peer Reviewed
See detailPaving the future: finding suitable ISMB venues
Rost, B.; Gaasterland, T.; Lengauer, T. et al

in Bioinformatics (2012), 28(19), 2556-9

ISCB, the International Society for Computational Biology, organizes the largest event in the field of computational biology and bioinformatics, namely the annual ISMB, the international conference on ... [more ▼]

ISCB, the International Society for Computational Biology, organizes the largest event in the field of computational biology and bioinformatics, namely the annual ISMB, the international conference on Intelligent Systems for Molecular Biology. This year at ISMB 2012 in Long Beach, ISCB celebrated the 20th anniversary of its flagship meeting. ISCB is a young, lean and efficient society that aspires to make a significant impact with only limited resources. Many constraints make the choice of venues for ISMB a tough challenge. Here, we describe those challenges and invite the contribution of ideas for solutions. [less ▲]

Detailed reference viewed: 24 (1 UL)
Full Text
Peer Reviewed
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 ▲]

Detailed reference viewed: 63 (9 UL)
Full Text
Peer Reviewed
See detailReLiance: a machine learning and literature-based prioritization of receptor—ligand pairings.
Iacucci, Ernesto; Tranchevent, L. C.; Popovic, D. et al

in Bioinformatics (2012), 28(18), 569-574

Motivation: The prediction of receptor—ligand pairings is an important area of research as intercellular communications are mediated by the successful interaction of these key proteins. As the exhaustive ... [more ▼]

Motivation: The prediction of receptor—ligand pairings is an important area of research as intercellular communications are mediated by the successful interaction of these key proteins. As the exhaustive assaying of receptor—ligand pairs is impractical, a computational approach to predict pairings is necessary. We propose a workflow to carry out this interaction prediction task, using a text mining approach in conjunction with a state of the art prediction method, as well as a widely accessible and comprehensive dataset. Among several modern classifiers, random forests have been found to be the best at this prediction task. The training of this classifier was carried out using an experimentally validated dataset of Database of Ligand-Receptor Partners (DLRP) receptor—ligand pairs. New examples, co-cited with the training receptors and ligands, are then classified using the trained classifier. After applying our method, we find that we are able to successfully predict receptor—ligand pairs within the GPCR family with a balanced accuracy of 0.96. Upon further inspection, we find several supported interactions that were not present in the Database of Interacting Proteins (DIPdatabase). We have measured the balanced accuracy of our method resulting in high quality predictions stored in the available database ReLiance. Availability: http://homes.esat.kuleuven.be/?bioiuser/ReLianceDB/ index.php Contact: yves.moreau@esat.kuleuven.be; ernesto.iacucci@gmail. com Supplementary information: Supplementary data are available at Bioinformatics online [less ▲]

Detailed reference viewed: 20 (2 UL)
Full Text
Peer Reviewed
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 ▲]

Detailed reference viewed: 21 (2 UL)
Full Text
Peer Reviewed
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 ▲]

Detailed reference viewed: 25 (2 UL)
Full Text
Peer Reviewed
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 ▲]

Detailed reference viewed: 15 (0 UL)
Full Text
Peer Reviewed
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 ▲]

Detailed reference viewed: 16 (0 UL)
Full Text
Peer Reviewed
See detailMethyl side-chain dynamics prediction based on protein structure
Carbonell, P.; del Sol Mesa, Antonio UL

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

Detailed reference viewed: 20 (8 UL)
Full Text
Peer Reviewed
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)

Detailed reference viewed: 13 (0 UL)
Full Text
Peer Reviewed
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)

Detailed reference viewed: 24 (0 UL)