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See detailVariant Score Ranker - a web application for intuitive missense variant prioritization
Du, Juanjiangmeng; Sudarsanam, Monica; Pérez-Palma, Eduardo et al

in Bioinformatics (2019)

The correct classification of missense variants as benign or pathogenic remains challenging. Pathogenic variants are expected to have higher deleterious prediction scores than benign variants in the same ... [more ▼]

The correct classification of missense variants as benign or pathogenic remains challenging. Pathogenic variants are expected to have higher deleterious prediction scores than benign variants in the same gene. However, most of the existing variant annotation tools do not reference the score range of benign population variants on gene level. Here, we present a web-application, Variant Score Ranker, which enables users to rapidly annotate variants and perform gene-specific variant score ranking on the population level. We also provide an intuitive example of how gene- and population-calibrated variant ranking scores can improve epilepsy variant prioritization. [less ▲]

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See detailControlling large Boolean networks with single-step perturbations
Baudin, Alexis; Paul, Soumya UL; Su, Cui et al

in Bioinformatics (2019), 35(14), 558-567

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See detailThe Microbiome Modeling Toolbox: from microbial interactions to personalized microbial communities
Baldini, Federico UL; Heinken, Almut Katrin UL; Heirendt, Laurent UL et al

in Bioinformatics (2018)

The application of constraint-based modeling to functionally analyze metagenomic data has been limited so far, partially due to the absence of suitable toolboxes. To address this gap, we created a ... [more ▼]

The application of constraint-based modeling to functionally analyze metagenomic data has been limited so far, partially due to the absence of suitable toolboxes. To address this gap, we created a comprehensive toolbox to model i) microbe-microbe and host-microbe metabolic interactions, and ii) microbial communities using microbial genome-scale metabolic reconstructions and metagenomic data. The Microbiome Modeling Toolbox extends the functionality of the COBRA Toolbox. The Microbiome Modeling Toolbox and the tutorials at https://git.io/microbiomeModelingToolbox. [less ▲]

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See detailMolArt: a molecular structure annotation and visualization tool
Hoksza, David UL; Gawron, Piotr UL; Ostaszewski, Marek UL et al

in Bioinformatics (2018)

Summary MolArt fills the gap between sequence and structure visualization by providing a light-weight, interactive environment enabling exploration of sequence annotations in the context of available ... [more ▼]

Summary MolArt fills the gap between sequence and structure visualization by providing a light-weight, interactive environment enabling exploration of sequence annotations in the context of available experimental or predicted protein structures. Provided a UniProt ID, MolArt downloads and displays sequence annotations, sequence-structure mapping and relevant structures. The sequence and structure views are interlinked, enabling sequence annotations being color overlaid over the mapped structures, thus providing an enhanced understanding and interpretation of the available molecular data. Availability and implementation MolArt is released under the Apache 2 license and is available at https://github.com/davidhoksza/MolArt. The project web page https://davidhoksza.github.io/MolArt/ features examples and applications of the tool. [less ▲]

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See detailRapidRMSD: Rapid determination of RMSDs corresponding to motions of flexible molecules
Neveu, Emilie; Popov, Petr; Hoffmann, Alexandre et al

in Bioinformatics (2018)

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See detailPresenting and Sharing Clinical Data using the eTRIKS Standards Master Tree for tranSMART
Barbosa-Silva, Adriano; Bratfalean, Dorina; Gu, Wei UL et al

in Bioinformatics (2018)

Motivation Standardization and semantic alignment have been considered one of the major challenges for data integration in clinical research. The inclusion of the CDISC SDTM clinical data standard into ... [more ▼]

Motivation Standardization and semantic alignment have been considered one of the major challenges for data integration in clinical research. The inclusion of the CDISC SDTM clinical data standard into the tranSMART i2b2 via a guiding master ontology tree positively impacts and supports the efficacy of data sharing, visualization and exploration across datasets. Results We present here a schema for the organization of SDTM variables into the tranSMART i2b2 tree along with a script and test dataset to exemplify the mapping strategy. The eTRIKS master tree concept is demonstrated by making use of fictitious data generated for four patients, including 16 SDTM clinical domains. We describe how the usage of correct visit names and data labels can help to integrate multiple readouts per patient and avoid ETL crashes when running a tranSMART loading routine. Availability The eTRIKS Master Tree package and test datasets are publicly available at https://doi.org/10.5281/zenodo.1009098 and a functional demo installation at https://public.etriks.org/transmart/datasetExplorer/ under eTRIKS - Master Tree branch, where the discussed examples can be visualized. [less ▲]

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See detailCaSiAn: a Calcium Signaling Analyzer tool
Moein, Mahsa UL; Grzyb, Kamil UL; Gonçalves Martins, Teresa et al

in Bioinformatics (2018), 1

Ca2þ is a central second messenger in eukaryotic cells that regulates many cellular proc- esses. Recently, we have indicated that typical Ca2þ signals are not purely oscillatory as widely assumed, but ... [more ▼]

Ca2þ is a central second messenger in eukaryotic cells that regulates many cellular proc- esses. Recently, we have indicated that typical Ca2þ signals are not purely oscillatory as widely assumed, but exhibit stochastic spiking with cell type and pathway specific characteristics. Here, we present the Calcium Signaling Analyzer (CaSiAn), an open source software tool that allows for quantifying these signal characteristics including individual spike properties and time course statis- tics in a semi-automated manner. CaSiAn provides an intuitive graphical user interface allowing experimentalists to easily process a large amount of Ca2þ signals, interactively tune peak detection, revise statistical measures and access the quantified signal properties as excel or text files. [less ▲]

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See detailDistributedFBA.jl: High-level, high-performance flux balance analysis in Julia.
Heirendt, Laurent UL; Thiele, Ines UL; Fleming, Ronan MT UL

in Bioinformatics (2017)

MOTIVATION: Flux balance analysis, and its variants, are widely used methods for predicting steady-state reaction rates in biochemical reaction networks. The exploration of high dimensional networks with ... [more ▼]

MOTIVATION: Flux balance analysis, and its variants, are widely used methods for predicting steady-state reaction rates in biochemical reaction networks. The exploration of high dimensional networks with such methods is currently hampered by software performance limitations. RESULTS: DistributedFBA.jl is a high-level, high-performance, open-source implementation of flux balance analysis in Julia. It is tailored to solve multiple flux balance analyses on a subset or all the reactions of large and huge-scale networks, on any number of threads or nodes. AVAILABILITY: The code is freely available on github.com/opencobra/COBRA.jl. The documentation can be found at opencobra.github.io/COBRA.jl. [less ▲]

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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 ▲]

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See detailReconMap: An interactive visualisation of human metabolism
Noronha, Alberto UL; Danielsdóttir, Anna Dröfn; Jóhannsson, Freyr et al

in Bioinformatics (2016)

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 ▲]

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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 ▲]

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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 ▲]

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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 ▲]

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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 ▲]

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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 ▲]

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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 ▲]

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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 ▲]

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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: 64 (1 UL)