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{ "count": 370, "next": "?page=2", "previous": null, "list": [ { "name": "RiboGalaxy", "description": "Galaxy-based web server where researchers can pre-process, align, analyze and visualize their own ribosome profiling (ribo-seq) data. GUI-based tools are provided to determine the strength of the triplet periodicity signal in ribo-seq data, generate metagene and ribosome profiles and carry out differential translation expression analysis using the riboSeqR suite. The RUST suite of tools can be used to quickly characterize ribosome profiling datasets to assess their quality and more.", "homepage": "http://ribogalaxy.ucc.ie", "biotoolsID": "ribogalaxy", "biotoolsCURIE": "biotools:ribogalaxy", "version": [ "1" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" }, { "uri": "http://edamontology.org/operation_2928", "term": "Alignment" }, { "uri": "http://edamontology.org/operation_0314", "term": "Gene expression profiling" }, { "uri": "http://edamontology.org/operation_2495", "term": "Gene expression analysis" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0848", "term": "Raw sequence" }, "format": [ { "uri": "http://edamontology.org/format_1932", "term": "FASTQ-sanger" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2968", "term": "Image" }, "format": [ { "uri": "http://edamontology.org/format_3603", "term": "PNG" } ] }, { "data": { "uri": "http://edamontology.org/data_0863", "term": "Sequence alignment" }, "format": [ { "uri": "http://edamontology.org/format_2572", "term": "BAM" }, { "uri": "http://edamontology.org/format_3006", "term": "bigWig" } ] }, { "data": { "uri": "http://edamontology.org/data_2969", "term": "Sequence image" }, "format": [ { "uri": "http://edamontology.org/format_3603", "term": "PNG" } ] } ], "note": "Raw ribo-seq and mRNA-seq FASTQ files There are multiple outputs depending on the tool/jobs that are run. Most of the ribo-seq analysis tools provide the output in both spreadsheet and/or visual format.", "cmd": null } ], "toolType": [ "Workbench" ], "topic": [ { "uri": "http://edamontology.org/topic_0203", "term": "Gene expression" } ], "operatingSystem": [ "Windows", "Mac" ], "language": [], "license": null, "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [ "Galaxy" ], "link": [ { "url": "https://github.com/riboseqorg/RiboGalaxy", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [ { "url": "http://ribogalaxy.ucc.ie/static/conditions_of_use.html", "type": [ "Terms of use" ], "note": null }, { "url": "http://ribogalaxy.ucc.ie/", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1080/15476286.2016.1141862", "pmid": "26821742", "pmcid": "PMC4829337", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "RiboGalaxy: A browser based platform for the alignment, analysis and visualization of ribosome profiling data", "abstract": "Ribosome profiling (ribo-seq) is a technique that uses high-throughput sequencing to reveal the exact locations and densities of translating ribosomes at the entire transcriptome level. The technique has become very popular since its inception in 2009. Yet experimentalists who generate ribo-seq data often have to rely on bioinformaticians to process and analyze their data. We present RiboGalaxy (http://ribogalaxy.ucc.ie), a freely available Galaxy-based web server for processing and analyzing ribosome profiling data with the visualization functionality provided by GWIPS-viz (http://gwips.ucc.ie). RiboGalaxy offers researchers a suite of tools specifically tailored for processing ribo-seq and corresponding mRNA-seq data. Researchers can take advantage of the published workflows which reduce the multi-step alignment process to a minimum of inputs from the user. Users can then explore their own aligned data as custom tracks in GWIPS-viz and compare their ribosome profiles to existing ribo-seq tracks from published studies. In addition, users can assess the quality of their ribo-seq data, determine the strength of the triplet periodicity signal, generate meta-gene ribosome profiles as well as analyze the relative impact of mRNA sequence features on local read density. RiboGalaxy is accompanied by extensive documentation and tips for helping users. In addition we provide a forum (http://gwips.ucc.ie/Forum) where we encourage users to post their questions and feedback to improve the overall RiboGalaxy service.", "date": "2016-03-03T00:00:00Z", "citationCount": 67, "authors": [ { "name": "Michel A.M." }, { "name": "Mullan J.P.A." }, { "name": "Velayudhan V." }, { "name": "O'Connor P.B.F." }, { "name": "Donohue C.A." }, { "name": "Baranov P.V." } ], "journal": "RNA Biology" } }, { "doi": "10.1016/J.JMB.2023.168043", "pmid": "37356899", "pmcid": null, "type": [ "Review" ], "version": null, "note": null, "metadata": { "title": "RiboGalaxy: A Galaxy-based Web Platform for Ribosome Profiling Data Processing – 2023 Update", "abstract": "Ribosome profiling (Ribo-Seq) captures a “snapshot” of ribosomes’ locations at the entire transcriptome of a cell at sub-codon resolution providing insights into gene expression and enabling the discovery of novel translated regions. RiboGalaxy (https://ribogalaxy.genomicsdatascience.ie/), a Galaxy-based platform for processing Ribo-Seq data is a RiboSeq.Org (https://riboseq.org/) resource. RiboSeq.Org is an online gateway to a set of integrated tools for the processing and analysis of Ribo-Seq data. In this RiboGalaxy update we introduce changes to both the tools available on RiboGalaxy and to how the resource is managed on the backend. For example, in order to improve interoperability between Riboseq.Org resources, we added tools that link RiboGalaxy outputs with Trips-Viz and GWIPS-viz browsers for downstream analysis and visualisation. RiboGalaxy's backend now utilises Ansible configuration management which enhances its stability and jobs are executed within Singularity containers and are managed by Slurm, strengthening reproducibility and performance respectively.", "date": "2023-07-15T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Fedorova A.D." }, { "name": "Tierney J.A.S." }, { "name": "Michel A.M." }, { "name": "Baranov P.V." } ], "journal": "Journal of Molecular Biology" } } ], "credit": [ { "name": "Science Foundation Ireland", "email": "info@sfi.ie", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": "ucc.ie", "email": null, "url": "http://www.ucc.ie", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": null, "email": "ribogalaxy@gmail.com", "url": "http://ribogalaxy.ucc.ie/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Pavel V. Baranov", "email": "p.baranov@ucc.ie", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "community": null, "owner": "A.Michel@ucc.ie", "additionDate": "2016-05-24T10:51:12Z", "lastUpdate": "2024-02-23T09:02:01.891026Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Integron Finder", "description": "A tool to detect Integron in DNA sequences.", "homepage": "https://github.com/gem-pasteur/Integron_Finder", "biotoolsID": "integron_finder", "biotoolsCURIE": "biotools:integron_finder", "version": [ "1.5.1", "2.0.1", "2.0.2", "2.0.3" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0415", "term": "Nucleic acid feature detection" }, { "uri": "http://edamontology.org/operation_0239", "term": "Sequence motif recognition" }, { "uri": "http://edamontology.org/operation_3092", "term": "Protein feature detection" }, { "uri": "http://edamontology.org/operation_0362", "term": "Genome annotation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3497", "term": "DNA sequence (raw)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0849", "term": "Sequence record" }, "format": [ { "uri": "http://edamontology.org/format_1936", "term": "GenBank format" } ] }, { "data": { "uri": "http://edamontology.org/data_1270", "term": "Feature table" }, "format": [ { "uri": "http://edamontology.org/format_3475", "term": "TSV" } ] } ], "note": "Single fasta file", "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0085", "term": "Functional genomics" }, { "uri": "http://edamontology.org/topic_0798", "term": "Mobile genetic elements" }, { "uri": "http://edamontology.org/topic_3047", "term": "Molecular biology" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" } ], "operatingSystem": [ "Linux", "Mac" ], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [ "GEM Pasteur" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/gem-pasteur/Integron_Finder/", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [ { "url": "http://integronfinder.readthedocs.org/", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkw319", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": "1.5.1", "note": null, "metadata": { "title": "Identification and analysis of integrons and cassette arrays in bacterial genomes", "abstract": "Integrons recombine gene arrays and favor the spread of antibiotic resistance. Their broader roles in bacterial adaptation remain mysterious, partly due to lack of computational tools. We made a program-IntegronFinder-to identify integrons with high accuracy and sensitivity. IntegronFinder is available as a standalone program and as a web application. It searches for attC sites using covariance models, for integron-integrases using HMM profiles, and for other features (promoters, attI site) using pattern matching. We searched for integrons, integron-integrases lacking attC sites, and clusters of attC sites lacking a neighboring integron-integrase in bacterial genomes. All these elements are especially frequent in genomes of intermediate size. They are missing in some key phyla, such as α-Proteobacteria, which might reflect selection against cell lineages that acquire integrons. The similarity between attC sites is proportional to the number of cassettes in the integron, and is particularly low in clusters of attC sites lacking integron-integrases. The latter are unexpectedly abundant in genomes lacking integron-integrases or their remains, and have a large novel pool of cassettes lacking homologs in the databases. They might represent an evolutionary step between the acquisition of genes within integrons and their stabilization in the new genome.", "date": "2016-06-02T00:00:00Z", "citationCount": 186, "authors": [ { "name": "Cury J." }, { "name": "Jove T." }, { "name": "Touchon M." }, { "name": "Neron B." }, { "name": "Rocha E.P." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.3390/microorganisms10020224", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": "2.0.1", "note": null, "metadata": { "title": "Integron Functionality and Genome Innovation: An Update on the Subtle and Smart Strategy of Integrase and Gene Cassette Expression Regulation", "abstract": "Integrons are considered hot spots for bacterial evolution, since these platforms allow one-step genomic innovation by capturing and expressing genes that provide advantageous novelties, such as antibiotic resistance. The acquisition and shuffling of gene cassettes featured by integrons enable the population to rapidly respond to changing selective pressures. However, in order to avoid deleterious effects and fitness burden, the integron activity must be tightly controlled, which happens in an elegant and elaborate fashion, as discussed in detail in the present review. Here, we aimed to provide an up‐to‐date overview of the complex regulatory networks that permeate the expression and functionality of integrons at both transcriptional and translational levels. It was possible to compile strong shreds of evidence clearly proving that these versatile platforms include functions other than acquiring and expressing gene cassettes. The well‐balanced mechanism of integron expression is intricately related with environmental signals, host cell physiology, fitness, and survival, ultimately leading to adaptation on the demand.", "date": "2022-02-01T00:00:00Z", "citationCount": 9, "authors": [ { "name": "Fonseca E.L." }, { "name": "Vicente A.C." } ], "journal": "Microorganisms" } } ], "credit": [ { "name": "Institut Pasteur", "email": null, "url": "http://www.pasteur.fr/en", "orcidid": null, "gridid": "grid.428999.7", "rorid": "0495fxg12", "fundrefid": "10.13039/501100003762", "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "C3BI", "email": null, "url": "https://research.pasteur.fr/en/center/c3bi/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Division", "typeRole": [], "note": null }, { "name": "ERC EVOMOBILOME", "email": null, "url": "https://erc.europa.eu/projects-and-results/erc-funded-projects/evomobilome", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": "Jean Cury", "email": "jean.cury@normalesup.org", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Support" ], "note": null }, { "name": "Bertrand Neron", "email": "bneron@pasteur.fr", "url": null, "orcidid": "https://orcid.org/0000-0002-0220-0482", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Eduardo Rocha", "email": "eduardo.rocha@pasteur.fr", "url": "https://research.pasteur.fr/fr/member/eduardo-rocha/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Support" ], "note": null }, { "name": "Microbial Evolutionary Genomics", "email": null, "url": "https://research.pasteur.fr/en/team/microbial-evolutionary-genomics/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Division", "typeRole": [], "note": "CNRS - UMR 352" }, { "name": "Jean Cury", "email": "jean.cury@normalesup.org", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Bertrand Neron", "email": "bneron@pasteur.fr", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Eduardo Rocha", "email": "eduardo.rocha@pasteur.fr", "url": "https://research.pasteur.fr/fr/member/eduardo-rocha/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Eloi Littner", "email": "eloi.littner@pasteur.fr", "url": null, "orcidid": "https://orcid.org/0000-0002-8793-9584", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Matthieu Haudiquet", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-0878-2209", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Amandine PERRIN", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-4797-6185", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "INCEPTION", "email": null, "url": "https://anr.fr/ProjetIA-16-CONV-0005", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": "Laboratoire d’Excellence IBEID Integrative Biology of Emerging Infectious Diseases", "email": null, "url": "https://anr.fr/ProjetIA-10-LABX-0062", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null } ], "community": null, "owner": "jeanrjc", "additionDate": "2016-11-28T10:07:17Z", "lastUpdate": "2024-02-14T13:27:58.376472Z", "editPermission": { "type": "group", "authors": [ "hmenager", "khillion", "bneron" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "AltaiR", "description": "AltaiR is a C toolkit for alignment-free and spatial-temporal analysis of multi-FASTA data.\n\nThis method provides alignment-free and spatial-temporal analysis of multi-FASTA data through the implementation of a C toolkit that is highly flexible and with characteristics covering large-scale data, namely extensive collections of genomes/proteomes. This toolkit is ideal for scenarios entangling the presence of multiple sequences from epidemic and pandemic events. AlcoR is implemented in C language using multi-threading to increase the computational speed, is flexible for multiple applications, and does not contain external dependencies. The tool accepts any sequence(s) in (multi-) FASTA format.", "homepage": "https://github.com/cobilab/altair", "biotoolsID": "altair", "biotoolsCURIE": "biotools:altair", "version": [ "1.0.1" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2403", "term": "Sequence analysis" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" }, { "uri": "http://edamontology.org/topic_3307", "term": "Computational biology" }, { "uri": "http://edamontology.org/topic_3308", "term": "Transcriptomics" }, { "uri": "http://edamontology.org/topic_3303", "term": "Medicine" } ], "operatingSystem": [ "Linux" ], "language": [ "C" ], "license": "GPL-3.0", "collectionID": [ "COVID-19", "Rare Disease" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Tools", "Data" ], "elixirNode": [ "Portugal" ], "elixirCommunity": [], "link": [ { "url": "https://github.com/cobilab/altair", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [], "publication": [], "credit": [ { "name": "Jorge M. Silva", "email": "jorge.miguel.ferreira.silva@ua.pt", "url": null, "orcidid": "http://orcid.org/0000-0002-6331-6091", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Project", "typeRole": [ "Contributor" ], "note": "Researcher at IEETA. J.M.S. has received funding from the EC under grant agreement 101081813, Genomic Data Infrastructure." }, { "name": "Diogo Pratas", "email": "pratas@ua.pt", "url": null, "orcidid": "http://orcid.org/0000-0003-1176-552X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": "Researcher at IEETA. D.P. is funded by national funds through FCT – Fundação para a Ciência e a Tecnologia, I.P., under the Scientific Employment Stimulus - Institutional Call - reference CEECINST/00026/2018." } ], "community": null, "owner": "jorgeMFS", "additionDate": "2023-12-13T14:54:35.138186Z", "lastUpdate": "2023-12-13T14:54:35.146893Z", "editPermission": { "type": "group", "authors": [ "pratas" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "MrBayes", "description": "Program for Bayesian inference and model choice across a wide range of phylogenetic and evolutionary models. It uses Markov chain Monte Carlo (MCMC) methods to estimate the posterior distribution of model parameters.", "homepage": "http://nbisweden.github.io/MrBayes/", "biotoolsID": "mrbayes", "biotoolsCURIE": "biotools:mrbayes", "version": [ "3.2.6" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0547", "term": "Phylogenetic tree generation (maximum likelihood and Bayesian methods)" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3293", "term": "Phylogenetics" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "C" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/NBISweden/MrBayes", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://github.com/NBISweden/MrBayes/releases/tag/v3.2.6", "type": "Source code", "note": null, "version": null }, { "url": "https://github.com/NBISweden/MrBayes/releases/tag/v3.2.6", "type": "Binaries", "note": null, "version": null } ], "documentation": [ { "url": "https://github.com/NBISweden/MrBayes/blob/develop/COPYING", "type": [ "Terms of use" ], "note": null }, { "url": "http://nbisweden.github.io/MrBayes/", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/17.8.754", "pmid": "11524383", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "MRBAYES: Bayesian inference of phylogenetic trees", "abstract": "Summary: The program MRBAYES performs Bayesian inference of phylogeny using a variant of Markov chain Monte Carlo.", "date": "2001-01-01T00:00:00Z", "citationCount": 18632, "authors": [ { "name": "Huelsenbeck J.P." }, { "name": "Ronquist F." } ], "journal": "Bioinformatics" } }, { "doi": "10.1093/bioinformatics/btg180", "pmid": "12912839", "pmcid": null, "type": [], "version": "3", "note": null, "metadata": { "title": "MrBayes 3: Bayesian phylogenetic inference under mixed models", "abstract": "Summary: MrBayes 3 performs Bayesian phylogenetic analysis combining information from different data partitions or subsets evolving under different stochastic evolutionary models. This allows the user to analyze heterogeneous data sets consisting of different data types - e.g. morphological, nucleotide, and protein - and to explore a wide variety of structured models mixing partition-unique and shared parameters. The program employs MPI to parallelize Metropolis coupling on Macintosh or UNIX clusters.", "date": "2003-08-12T00:00:00Z", "citationCount": 24269, "authors": [ { "name": "Ronquist F." }, { "name": "Huelsenbeck J.P." } ], "journal": "Bioinformatics" } }, { "doi": "10.1093/sysbio/sys029", "pmid": "22357727", "pmcid": "PMC3329765", "type": [], "version": "3.2", "note": null, "metadata": { "title": "Mrbayes 3.2: Efficient bayesian phylogenetic inference and model choice across a large model space", "abstract": "Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site dN/dS rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software. © 2012 The Author(s).", "date": "2012-05-01T00:00:00Z", "citationCount": 15381, "authors": [ { "name": "Ronquist F." }, { "name": "Teslenko M." }, { "name": "Van Der Mark P." }, { "name": "Ayres D.L." }, { "name": "Darling A." }, { "name": "Hohna S." }, { "name": "Larget B." }, { "name": "Liu L." }, { "name": "Suchard M.A." }, { "name": "Huelsenbeck J.P." } ], "journal": "Systematic Biology" } } ], "credit": [ { "name": "Fredrik Ronquist", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Paul van der Mark", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Contributor" ], "note": null }, { "name": "Maxim Teslenko", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Contributor" ], "note": null }, { "name": "Donald Simon", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Contributor" ], "note": null }, { "name": "John Huelsenbeck", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Contributor" ], "note": null }, { "name": "Bret Larget", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Contributor" ], "note": null }, { "name": "Chi Zhang", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Contributor" ], "note": null }, { "name": "Dept. of Biodiversity Informatics at the Swedish Museum of Natural History", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Vetenskapsrådet", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": "NSF", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": "NIH", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": "icm.uu.se", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": null, "email": null, "url": "http://nbisweden.github.io/MrBayes/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "community": null, "owner": "andreas.kahari@icm.uu.se", "additionDate": "2016-04-21T06:14:09Z", "lastUpdate": "2023-11-03T08:32:13.053903Z", "editPermission": { "type": "group", "authors": [ "sergitobara", "EngyNasr" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Clustal 2 (Clustal W, Clustal X)", "description": "Multiple sequence alignment program with a command-line interface (Clustal W) and a graphical user interface (Clustal X). 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Since 2005, the Galaxy project has fostered a global community focused on achieving accessible, reproducible, and collaborative research. Together, this community develops the Galaxy software framework, integrates analysis tools and visualizations into the framework, runs public servers that make Galaxy available via a web browser, performs and publishes analyses using Galaxy, leads bioinformatics workshops that introduce and use Galaxy, and develops interactive training materials for Galaxy. Over the last two years, all aspects of the Galaxy project have grown: code contributions, tools integrated, users, and training materials. Key advances in Galaxy’s user interface include enhancements for analyzing large dataset collections as well as interactive tools for exploratory data analysis. Extensions to Galaxy’s framework include support for federated identity and access management and increased ability to distribute analysis jobs to remote resources. 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Some of these staff are part funded by QCIF sourced funds." }, { "name": "Melbourne Bioinformatics", "email": null, "url": "https://www.melbournebioinformatics.org.au/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": "Staff based at Melbourne Bioinformatics manage the Galaxy Australia service. Some of these staff are part funded by the University of Melbourne." }, { "name": "Australian BioCommons", "email": null, "url": "https://www.biocommons.org.au/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Project", "typeRole": [], "note": "It is the mission of the Australian BioCommons to To provide access to services that enable sophisticated life science data analysis capabilities, including software and hardware platforms. Galaxy Australia is the flagship service of the Australian BioCommons." } ], "community": null, "owner": "jchrist", "additionDate": "2018-11-20T06:38:59Z", "lastUpdate": "2023-09-26T22:49:04.577938Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "GRNsight", "description": "Web application and service for visualizing small- to medium-scale models of gene regulatory networks. It automatically lays out either an unweighted or weighted network graph based on an Excel input spreadsheet containing an adjacency matrix where regulators are named in the columns and target genes in the rows. It is best-suited for visualizing networks of fewer than 35 nodes and 70 edges and has general applicability.", "homepage": "http://dondi.github.io/GRNsight/", "biotoolsID": "grnsight", "biotoolsCURIE": "biotools:grnsight", "version": [ "6.0.7" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_1781", "term": "Gene regulatory network analysis" }, { "uri": "http://edamontology.org/operation_3083", "term": "Pathway or network visualisation" } ], "input": [], "output": [], "note": "GRNsight automatically lays out a network graph based on an Excel input spreadsheet containing an adjacency matrix where regulators are named in the columns and target genes in the rows. When a user uploads a spreadsheet with an unweighted adjacency matrix, GRNsight automatically lays out the graph using black lines and pointed arrowheads. When a user uploads a spreadsheet with a weighted adjacency matrix, GRNsight uses pointed and blunt arrowheads, and colors the edges and adjusts their thicknesses based on the sign (positive for activation or negative for repression) and magnitude of the weight parameter. Nodes are rectangular and support gene labels of up to 12 characters. The edges are arcs, which become straight lines when the nodes are close together. Self-regulatory edges are indicated by a loop on the lower-right side of a node. Visualizations can be modified by sliders that adjust D3.js's force graph layout parameters and through manual node dragging.", "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0602", "term": "Molecular interactions, pathways and networks" }, { "uri": "http://edamontology.org/topic_0204", "term": "Gene regulation" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "JavaScript" ], "license": "BSD-3-Clause", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/dondi/GRNsight", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://github.com/dondi/GRNsight/archive/master.zip", "type": "Source code", "note": null, "version": null } ], "documentation": [ { "url": "http://dondi.github.io/GRNsight/documentation.html", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.7717/peerj-cs.85", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "GRNsight: A web application and service for visualizing models of small-to medium-scale gene regulatory networks", "abstract": "GRNsight is a web application and service for visualizing models of gene regulatory networks (GRNs). A gene regulatory network (GRN) consists of genes, transcription factors, and the regulatory connections between them which govern the level of expression of mRNA and protein from genes. The original motivation came from our efforts to perform parameter estimation and forward simulation of the dynamics of a differential equations model of a small GRN with 21 nodes and 31 edges. We wanted a quick and easy way to visualize the weight parameters from the model which represent the direction and magnitude of the influence of a transcription factor on its target gene, so we created GRNsight. GRNsight automatically lays out either an unweighted or weighted network graph based on an Excel spreadsheet containing an adjacency matrix where regulators are named in the columns and target genes in the rows, a Simple Interaction Format (SIF) text file, or a GraphML XML file. When a user uploads an input file specifying an unweighted network, GRNsight automatically lays out the graph using black lines and pointed arrowheads. For a weighted network, GRNsight uses pointed and blunt arrowheads, and colors the edges and adjusts their thicknesses based on the sign (positive for activation or negative for repression) and magnitude of the weight parameter. GRNsight is written in JavaScript, with diagrams facilitated by D3.js, a data visualization library. Node.js and the Express framework handle server-side functions. GRNsight's diagrams are based on D3.js's force graph layout algorithm, which was then extensively customized to support the specific needs of GRNs. Nodes are rectangular and support gene labels of up to 12 characters. The edges are arcs, which become straight lines when the nodes are close together. Self-regulatory edges are indicated by a loop.When a user mouses over an edge, the numerical value of the weight parameter is displayed. Visualizations can be modified by sliders that adjust the force graph layout parameters and through manual node dragging. GRNsight is best-suited for visualizing networks of fewer than 35 nodes and 70 edges, although it accepts networks of up to 75 nodes or 150 edges. GRNsight has general applicability for displaying any small, unweighted or weighted network with directed edges for systems biology or other application domains. GRNsight serves as an example of following and teaching best practices for scientific computing and complying with FAIR principles, using an open and test-driven development model with rigorous documentation of requirements and issues on GitHub. An exhaustive unit testing framework using Mocha and the Chai assertion library consists of around 160 automated unit tests that examine nearly 530 test files to ensure that the program is running as expected. The GRNsight application (http://dondi.github.io/ GRNsight/) and code (https://github.com/dondi/GRNsight) are available under the open source BSD license.", "date": "2016-01-01T00:00:00Z", "citationCount": 2, "authors": [ { "name": "Dahlquist K.D." }, { "name": "Dionisio J.D.N." }, { "name": "Fitzpatrick B.G." }, { "name": "Anguiano N.A." }, { "name": "Varshneya A." }, { "name": "Southwick B.J." }, { "name": "Samdarshi M." } ], "journal": "PeerJ Computer Science" } }, { "doi": "10.5281/zenodo.7411630", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": "Ona O. Igbinedion", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Ahmad R. Mersaghian", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Ian M. Green", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Lauren L. Amparo", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Alexia M. Filler", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Kevin B. Patterson", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "John L. 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Torres", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Eileen Choe", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Jen Shin", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Mihir Samdarshi", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Anindita Varshneya", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Nicole A. 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Dionisio", "email": "dondi@lmu.edu", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "community": null, "owner": "dondi@lmu.edu", "additionDate": "2016-08-13T19:15:03Z", "lastUpdate": "2023-08-29T16:51:15.145002Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "CarveMe", "description": "CarveMe is a python-based automated tool used for top-down genome-scale metabolic model reconstruction. It can predict an organism's uptake and secretion capabilities without requiring gap-filling, although gap-filling is also supported. Additionally, CarveMe allows the generation of microbial community models by merging single species models. The tool offers advanced features such as manual adjustment of blasting options, an orthology-based search using eggNOG-mapper (kegg-bigg branch), the ability to provide a custom media library for gap-filling, and the generation of models compatible with various SBML formats. Furthermore, CarveMe supports ensemble modeling, which helps explore how different alternative solutions can lead to diverse network structures and predict various phenotypes. 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Yet, the application of genome-scale models, especially to microbial communities, is lagging behind the availability of sequenced genomes. This is largely due to the time-consuming steps of manual curation required to obtain good quality models. Here, we present an automated tool, CarveMe, for reconstruction of species and community level metabolic models. We introduce the concept of a universal model, which is manually curated and simulation ready. Starting with this universal model and annotated genome sequences, CarveMe uses a topdown approach to build single-species and community models in a fast and scalable manner. We show that CarveMe models perform closely to manually curated models in reproducing experimental phenotypes (substrate utilization and gene essentiality). Additionally, we build a collection of 74 models for human gut bacteria and test their ability to reproduce growth on a set of experimentally defined media. Finally, we create a database of 5587 bacterial models and demonstrate its potential for fast generation of microbial community models. Overall, CarveMe provides an open-source and user-friendly tool towards broadening the use of metabolic modeling in studying microbial species and communities.", "date": "2018-09-06T00:00:00Z", "citationCount": 239, "authors": [ { "name": "Machado D." }, { "name": "Andrejev S." }, { "name": "Tramontano M." }, { "name": "Patil K.R." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1038/s41559-022-01939-0", "pmid": "36471121", "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "Reply to: Erroneous predictions of auxotrophies by CarveMe", "abstract": "", "date": "2023-02-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Machado D." }, { "name": "Patil K.R." } ], "journal": "Nature Ecology and Evolution" } } ], "credit": [ { "name": "Daniel Machado", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-2063-5383", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer", "Documentor", "Maintainer" ], "note": null }, { "name": "The Norwegian Bioinformatics Platform (ELIXIR-Norway) Helpdesk", "email": "support@elixir.no", "url": "https://elixir.no/helpdesk", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Consortium", "typeRole": [ "Support" ], "note": null }, { "name": "Sergej Andrejev", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-7875-0261", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Melanie Tramontano", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0001-6407-527X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Kiran Raosaheb Patil", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-6166-8640", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "NTNU", "email": null, "url": "http://www.ntnu.edu", "orcidid": null, "gridid": "grid.5947.f", "rorid": "05xg72x27", "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": "Developed at NTNU 2020-present" }, { "name": "European Molecular Biology Laboratory (EMBL)", "email": null, "url": "http://embl.org/", "orcidid": null, "gridid": "grid.4709.a", "rorid": "03mstc592", "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": "Developed at EMBL 2017-2019" }, { "name": "European Union's Horizon 2020", "email": null, "url": "https://doi.org/10.3030/686070", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [], "note": null }, { "name": "Erin Calhoun", "email": "erin.calhoun@uit.no", "url": null, "orcidid": "https://orcid.org/0009-0003-3752-7156", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Documentor" ], "note": "Curation of bio.tools profile - contact me with updates/corrections." } ], "community": null, "owner": "dmachado", "additionDate": "2021-02-18T12:08:51Z", "lastUpdate": "2023-08-15T10:51:32.592010Z", "editPermission": { "type": "group", "authors": [ "eca008" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "omnipy", "description": "Omnipy is a Python library for type-driven data wrangling and scalable data flow orchestration. It simplifies creation and deployment of (meta)data transformation processes, emphasizing FAIRification, executable metadata crosswalks and data brokering. Omnipy aids generic data tasks like extraction from multiple sources, (meta)data mapping and systematic data model transformations. Embracing a \"parse, don't validate\" approach, omnipy uses Python type hints and pydantic for data consistency and adherence to specific models. Highly modular, it allows integration of (meta)data transformation steps dependent on software like pandas and R. The architecture supports pluggable execution engines like Prefect, a highly interoperable industry-developed Open Source data flow orchestration engine. Envisioned as a community effort, omnipy aims to offer various import formats and data models (both hierarchical and tabular representations), as well as ontology mapping and semiautomatic data cleaning.", "homepage": "https://fairtracks.net/fair/#fair-07-transformation", "biotoolsID": "omnipy", "biotoolsCURIE": "biotools:omnipy", "version": [ "0.10.4" ], "otherID": [], "relation": [ { "biotoolsID": "pandas", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2422", "term": "Data retrieval" }, { "uri": "http://edamontology.org/operation_3763", "term": "Service invocation" }, { "uri": "http://edamontology.org/operation_2429", "term": "Mapping" }, { "uri": "http://edamontology.org/operation_3695", "term": "Filtering" }, { "uri": "http://edamontology.org/operation_0335", "term": "Formatting" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2093", "term": "Data reference" }, "format": [ { "uri": "http://edamontology.org/format_3996", "term": "Python script" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2080", "term": "Database search results" }, "format": [ { "uri": "http://edamontology.org/format_3464", "term": "JSON" } ] } ], "note": "Import diverse data from API endpoints (JSON) and relational databases. Output as JSON files specifying fields from the mapping API or as pandas DataFrames with reference metadata.", "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_3357", "term": "Format detection" }, { "uri": "http://edamontology.org/operation_1812", "term": "Parsing" }, { "uri": "http://edamontology.org/operation_0335", "term": "Formatting" }, { "uri": "http://edamontology.org/operation_3096", "term": "Editing" }, { "uri": "http://edamontology.org/operation_3359", "term": "Splitting" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2526", "term": "Text data" }, "format": [ { "uri": "http://edamontology.org/format_3464", "term": "JSON" }, { "uri": "http://edamontology.org/format_3475", "term": "TSV" }, { "uri": "http://edamontology.org/format_2333", "term": "Binary format" }, { "uri": "http://edamontology.org/format_3775", "term": "GSuite" }, { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2082", "term": "Matrix" }, "format": [] } ], "note": "Import data as files in a supported format. Output as pandas DataFrames with embedded JSON objects/lists and reference metadata.", "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_3435", "term": "Standardisation and normalisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2082", "term": "Matrix" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2082", "term": "Matrix" }, "format": [] } ], "note": "Data cleanup and transformation.", "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_2429", "term": "Mapping" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2082", "term": "Matrix" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0954", "term": "Database cross-mapping" }, "format": [] } ], "note": "Manual mapping of FAIRtracks objects and attributes to corresponding tables and columns in the original data.", "cmd": null }, { "operation": [ { "uri": 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"uri": "http://edamontology.org/operation_2428", "term": "Validation" }, { "uri": "http://edamontology.org/operation_0336", "term": "Format validation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_3365", "term": "Data architecture, analysis and design" }, { "uri": "http://edamontology.org/topic_3345", "term": "Data identity and mapping" }, { "uri": "http://edamontology.org/topic_3366", "term": "Data integration and warehousing" }, { "uri": "http://edamontology.org/topic_3473", "term": "Data mining" }, { "uri": "http://edamontology.org/topic_3572", "term": "Data quality management" }, { "uri": "http://edamontology.org/topic_0219", "term": "Data submission, annotation and curation" }, { "uri": "http://edamontology.org/topic_0089", "term": "Ontology and terminology" }, { "uri": "http://edamontology.org/topic_0769", "term": "Workflows" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Python" ], "license": "Apache-2.0", "collectionID": [ "ELIXIR-NO", "ELIXIR-Norway", "UiO tools" ], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Norway" ], "elixirCommunity": [ "3D-BioInfo", "Federated Human Data", "Human Copy Number Variation", "Intrinsically Disordered Proteins", "Marine Metagenomics", "Metabolomics", "Microbial Biotechnology", "Plant Sciences", "Proteomics", "Rare Diseases" ], "link": [ { "url": "https://pypi.org/project/omnipy/", "type": [ "Repository" ], "note": "PyPI page for omnipy" }, { "url": "https://github.com/fairtracks/omnipy", "type": [ "Issue tracker", "Repository" ], "note": null }, { "url": "https://github.com/fairtracks/omnipy_examples", "type": [ "Repository" ], "note": "Example projects using the omnipy package" }, { "url": "https://fairtracks.net/", "type": [ "Service" ], "note": "Omnipy was developed as part of the FAIRtracks project" }, { "url": "https://www.prefect.io/", "type": [ "Other" ], "note": "The Prefect workflow orchestration platform" } ], "download": [ { "url": "https://pypi.org/project/omnipy/#files", "type": "Source code", "note": "Latest release (still under development)", "version": "0.10.4" } ], "documentation": [ { "url": "https://omnipy.readthedocs.io/en/latest/", "type": [ "API documentation" ], "note": null } ], "publication": [], "credit": [ { "name": "Sveinung Gundersen", "email": "sveinugu@gmail.com", "url": null, "orcidid": "https://orcid.org/0000-0001-9888-7954", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer", "Documentor", "Maintainer", "Support" ], "note": null }, { "name": "Pável Vázquez", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-0471-9517", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Documentor", "Support" ], "note": null }, { "name": "Federico Bianchini", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-9016-4820", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Joshua Baskaran", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Jeanne Cheneby", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-4553-3110", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Ahmed Ghanem", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-2006-4242", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Eivind Hovig", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-9103-1077", "gridid": null, "rorid": 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"Contributing to Biohackathon projects (Oct-Nov 2023) related to omnipy" }, { "name": "Timo Mühlhaus", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-3925-6778", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": "Contributing to Biohackathon projects (Oct-Nov 2023) related to omnipy" }, { "name": "Sebastian Beier", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-2177-8781", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": "Contributing to Biohackathon projects (Oct-Nov 2023) related to omnipy" }, { "name": "Stuart Owen", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-2130-0865", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": "Contributing to Biohackathon projects (Oct-Nov 2023) related to omnipy" }, { "name": "Erin Calhoun", "email": "erin.calhoun@uit.no", "url": null, "orcidid": "https://orcid.org/0009-0003-3752-7156", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Documentor" ], "note": "Curation of bio.tools record - please contact me with updates/corrections." } ], "community": null, "owner": "eca008", "additionDate": "2023-08-10T08:23:57.988811Z", "lastUpdate": "2023-08-15T07:24:18.092241Z", "editPermission": { "type": "group", "authors": [ "matus.kalas@uib.no", "ELIXIR-NO", "UiO", "UiT" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "JASPAR", "description": "JASPAR is a high-quality, open-access database that provides manually curated, non-redundant transcription factor (TF) binding profiles for six taxonomic groups (fungi, insecta, nematoda, plantae, urochordata, vertebrata). These profiles are stored as position frequency matrices (PFMs), which can be transformed into models to predict TF binding sites (TFBS) in DNA sequences. The database collects motifs both internally, analyzing sequences using a custom motif discovery pipeline, and externally from publications and other resources. All selected motifs are manually curated for quality and supporting evidence. JASPAR now offers a tool for TFBS enrichment analysis in user-provided genomic regions. Data is accessible through the JASPAR website, its RESTful API, Bioconductor, or the Python package pyJASPAR.", "homepage": "http://jaspar.genereg.net/", "biotoolsID": "jaspar", "biotoolsCURIE": "biotools:jaspar", "version": [], "otherID": [ { "value": "RRID:SCR_003030", "type": "rrid", "version": null } ], "relation": [ { "biotoolsID": "jaspar_api", "type": "usedBy" }, { "biotoolsID": "tfbstools", "type": "usedBy" }, { "biotoolsID": "tfmotifview", "type": "usedBy" }, { "biotoolsID": "jaspextract", "type": "usedBy" }, { "biotoolsID": "aimodules", "type": "usedBy" }, { "biotoolsID": "bioconductor", "type": "uses" }, { "biotoolsID": "biocfilecache", "type": "uses" }, { "biotoolsID": "biopython", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2421", "term": "Database search" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2755", "term": "Transcription factor name" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1077", "term": "Transcription factor identifier" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1868", "term": "Taxon" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2732", "term": "Family name" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1045", "term": "Species name" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2291", "term": "UniProt ID" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_3671", "term": "Text" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1119", "term": "JASPAR profile ID" }, "format": [ { "uri": "http://edamontology.org/format_1367", "term": "JASPAR format" }, { "uri": "http://edamontology.org/format_3464", "term": "JSON" }, { "uri": "http://edamontology.org/format_2330", "term": "Textual format" }, { "uri": "http://edamontology.org/format_3752", "term": "CSV" }, { "uri": 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"http://edamontology.org/topic_0204", "term": "Gene regulation" }, { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" }, { "uri": "http://edamontology.org/topic_2815", "term": "Human biology" }, { "uri": "http://edamontology.org/topic_0780", "term": "Plant biology" }, { "uri": "http://edamontology.org/topic_0621", "term": "Model organisms" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Python" ], "license": "CC-BY-4.0", "collectionID": [ "ELIXIR-NO", "ELIXIR-Norway", "JASPAR" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Norway" ], "elixirCommunity": [ "Federated Human Data", "Plant Sciences" ], "link": [ { "url": "https://groups.google.com/g/jaspar", "type": [ "Discussion forum" ], "note": null }, { "url": "https://bitbucket.org/CBGR/jaspar/src/master/", "type": [ "Repository" ], "note": null }, { "url": "https://elixir.no/helpdesk", "type": [ "Helpdesk" ], "note": "Helpdesk and support for ELIXIR Norway services" }, { "url": "https://doi.org/10.5281/zenodo.6860527", "type": [ "Repository" ], "note": null }, { "url": "https://doi.org/10.5281/zenodo.6860555", "type": [ "Repository" ], "note": null }, { "url": "https://bioconductor.org/packages/release/data/annotation/html/JASPAR2022.html", "type": [ "Software catalogue" ], "note": null }, { "url": "https://pypi.org/project/pyjaspar/", "type": [ "Software catalogue" ], "note": null }, { "url": "https://twitter.com/jaspar_db", "type": [ "Social media" ], "note": null } ], "download": [ { "url": "http://jaspar.genereg.net/downloads/", "type": "Downloads page", "note": null, "version": null }, { "url": "https://jaspar.genereg.net/api/", "type": "API specification", "note": null, "version": null }, { "url": "https://github.com/asntech/pyjaspar", "type": "Source code", "note": "Repository for pyJASPAR", "version": null } ], "documentation": [ { "url": "http://jaspar.genereg.net/docs/", "type": [ "General", "Governance" ], "note": null }, { "url": "http://jaspar.genereg.net/faq/", "type": [ "FAQ" ], "note": null }, { "url": "http://jaspar.genereg.net/api/v1/docs/", "type": [ "API documentation" ], "note": null }, { "url": "https://pyjaspar.readthedocs.io/en/latest/", "type": [ "Citation instructions", "Command-line options", "Installation instructions", "User manual" ], "note": "Documentation for pyJASPAR" }, { "url": "https://bioconductor.org/packages/release/data/annotation/vignettes/JASPAR2022/inst/doc/JASPAR2022.html", "type": [ "Command-line options", "User manual" ], "note": "Documentation for the Bioconductor package" } ], "publication": [ { "doi": "10.1093/nar/gkab1113", "pmid": "34850907", "pmcid": "PMC8728201", "type": [ "Primary" ], "version": "9", "note": null, "metadata": { "title": "JASPAR 2022: The 9th release of the open-access database of transcription factor binding profiles", "abstract": "JASPAR (http://jaspar.genereg.net/) is an open-access database containing manually curated, non-redundant transcription factor (TF) binding profiles for TFs across six taxonomic groups. In this 9th release, we expanded the CORE collection with 341 new profiles (148 for plants, 101 for vertebrates, 85 for urochordates, and 7 for insects), which corresponds to a 19% expansion over the previous release. We added 298 new profiles to the Unvalidated collection when no orthogonal evidence was found in the literature. All the profiles were clustered to provide familial binding profiles for each taxonomic group. Moreover, we revised the structural classification of DNA binding domains to consider plant-specific TFs. This release introduces word clouds to represent the scientific knowledge associated with each TF. We updated the genome tracks of TFBSs predicted with JASPAR profiles in eight organisms; the human and mouse TFBS predictions can be visualized as native tracks in the UCSC Genome Browser. Finally, we provide a new tool to perform JASPAR TFBS enrichment analysis in user-provided genomic regions. All the data is accessible through the JASPAR website, its associated RESTful API, the R/Bioconductor data package, and a new Python package, pyJASPAR, that facilitates serverless access to the data.", "date": "2022-01-07T00:00:00Z", "citationCount": 356, "authors": [ { "name": "Castro-Mondragon J.A." }, { "name": "Riudavets-Puig R." }, { "name": "Rauluseviciute I." }, { "name": "Berhanu Lemma R." }, { "name": "Turchi L." }, { "name": "Blanc-Mathieu R." }, { "name": "Lucas J." }, { "name": "Boddie P." }, { "name": "Khan A." }, { "name": "Perez N.M." }, { "name": "Fornes O." }, { "name": "Leung T.Y." }, { "name": "Aguirre A." }, { "name": "Hammal F." }, { "name": "Schmelter D." }, { "name": "Baranasic D." }, { "name": "Ballester B." }, { "name": "Sandelin A." }, { "name": "Lenhard B." }, { "name": "Vandepoele K." }, { "name": "Wasserman W.W." }, { "name": "Parcy F." }, { "name": "Mathelier A." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkz1001", "pmid": "31701148", "pmcid": "PMC7145627", "type": [ "Primary" ], "version": "8", "note": null, "metadata": { "title": "JASPAR 2020: Update of the open-Access database of transcription factor binding profiles", "abstract": "JASPAR (http://jaspar.genereg.net) is an open-Access database of curated, non-redundant transcription factor (TF)-binding profiles stored as position frequency matrices (PFMs) for TFs across multiple species in six taxonomic groups. In this 8th release of JASPAR, the CORE collection has been expanded with 245 new PFMs (169 for vertebrates, 42 for plants, 17 for nematodes, 10 for insects, and 7 for fungi), and 156 PFMs were updated (125 for vertebrates, 28 for plants and 3 for insects). These new profiles represent an 18% expansion compared to the previous release. JASPAR 2020 comes with a novel collection of unvalidated TF-binding profiles for which our curators did not find orthogonal supporting evidence in the literature. This collection has a dedicated web form to engage the community in the curation of unvalidated TF-binding profiles. Moreover, we created a Q&A forum to ease the communication between the user community and JASPAR curators. Finally, we updated the genomic tracks, inference tool, and TF-binding profile similarity clusters. All the data is available through the JASPAR website, its associated RESTful API, and through the JASPAR2020 R/Bioconductor package.", "date": "2020-01-01T00:00:00Z", "citationCount": 996, "authors": [ { "name": "Fornes O." }, { "name": "Castro-Mondragon J.A." }, { "name": "Khan A." }, { "name": "Van Der Lee R." }, { "name": "Zhang X." }, { "name": "Richmond P.A." }, { "name": "Modi B.P." }, { "name": "Correard S." }, { "name": "Gheorghe M." }, { "name": "Baranasic D." }, { "name": "Santana-Garcia W." }, { "name": "Tan G." }, { "name": "Cheneby J." }, { "name": "Ballester B." }, { "name": "Parcy F." }, { "name": "Sandelin A." }, { "name": "Lenhard B." }, { "name": "Wasserman W.W." }, { "name": "Mathelier A." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkx1126", "pmid": "29140473", "pmcid": "PMC5753243", "type": [ "Primary" ], "version": "2018", "note": null, "metadata": { "title": "JASPAR 2018: Update of the open-access database of transcription factor binding profiles and its web framework", "abstract": "JASPAR (http://jaspar.genereg.net) is an open-access database of curated, non-redundant transcription factor (TF)-binding profiles stored as position frequency matrices (PFMs) and TF flexible models (TFFMs) for TFs across multiple species in six taxonomic groups. In the 2018 release of JASPAR, the CORE collection has been expanded with 322 new PFMs (60 for vertebrates and 262 for plants) and 33 PFMs were updated (24 for vertebrates, 8 for plants and 1 for insects). These new profiles represent a 30% expansion compared to the 2016 release. In addition, we have introduced 316 TFFMs (95 for vertebrates, 218 for plants and 3 for insects). This release incorporates clusters of similar PFMs in each taxon and each TF class per taxon. The JASPAR 2018 CORE vertebrate collection of PFMs was used to predict TF-binding sites in the human genome. The predictions are made available to the scientific community through a UCSC Genome Browser track data hub. Finally, this update comes with a new web framework with an interactive and responsive user-interface, along with new features. All the underlying data can be retrieved programmatically using a RESTful API and through the JASPAR 2018 R/Bioconductor package.", "date": "2018-01-01T00:00:00Z", "citationCount": 879, "authors": [ { "name": "Khan A." }, { "name": "Fornes O." }, { "name": "Stigliani A." }, { "name": "Gheorghe M." }, { "name": "Castro-Mondragon J.A." }, { "name": "Van Der Lee R." }, { "name": "Bessy A." }, { "name": "Cheneby J." }, { "name": "Kulkarni S.R." }, { "name": "Tan G." }, { "name": "Baranasic D." }, { "name": "Arenillas D.J." }, { "name": "Sandelin A." }, { "name": "Vandepoele K." }, { "name": "Lenhard B." }, { "name": "Ballester B." }, { "name": "Wasserman W.W." }, { "name": "Parcy F." }, { "name": "Mathelier A." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/bioinformatics/btx804", "pmid": "29253085", "pmcid": null, "type": [ "Usage" ], "version": null, "note": null, "metadata": { "title": "JASPAR RESTful API: Accessing JASPAR data from any programming language", "abstract": "JASPAR is a widely used open-access database of curated, non-redundant transcription factor binding profiles. Currently, data from JASPAR can be retrieved as flat files or by using programming language-specific interfaces. Here, we present a programming language-independent application programming interface (API) to access JASPAR data using the Representational State Transfer (REST) architecture. The REST API enables programmatic access to JASPAR by most programming languages and returns data in eight widely used formats. Several endpoints are available to access the data and an endpoint is available to infer the TF binding profile(s) likely bound by a given DNA binding domain protein sequence. Additionally, it provides an interactive browsable interface for bioinformatics tool developers. Availability and implementation This REST API is implemented in Python using the Django REST Framework. It is accessible at http://jaspar.genereg.net/api/ and the source code is freely available at https://bitbucket.org/CBGR/jaspar under GPL v3 license. Contact aziz.khan@ncmm.uio.no or anthony.mathelier@ncmm.uio.no Supplementary informationSupplementary dataare available at Bioinformatics online.", "date": "2018-05-01T00:00:00Z", "citationCount": 11, "authors": [ { "name": "Khan A." }, { "name": "Mathelier A." } ], "journal": "Bioinformatics" } }, { "doi": "10.1093/nar/gkv1176", "pmid": "26531826", "pmcid": null, "type": [ "Primary" ], "version": "2016", "note": null, "metadata": { "title": "JASPAR 2016: A major expansion and update of the open-access database of transcription factor binding profiles", "abstract": "JASPAR (http://jaspar.genereg.net) is an open-access database storing curated, non-redundant transcription factor (TF) binding profiles representing transcription factor binding preferences as position frequency matrices for multiple species in six taxonomic groups. For this 2016 release, we expanded the JASPAR CORE collection with 494 new TF binding profiles (315 in vertebrates, 11 in nematodes, 3 in insects, 1 in fungi and 164 in plants) and updated 59 profiles (58 in vertebrates and 1 in fungi). The introduced profiles represent an 83% expansion and 10% update when compared to the previous release. We updated the structural annotation of the TF DNA binding domains (DBDs) following a published hierarchical structural classification. In addition, we introduced 130 transcription factor flexible models trained on ChIP-seq data for vertebrates, which capture dinucleotide dependencies within TF binding sites. This new JASPAR release is accompanied by a new web tool to infer JASPAR TF binding profiles recognized by a given TF protein sequence. Moreover, we provide the users with a Ruby module complementing the JASPAR API to ease programmatic access and use of the JASPAR collection of profiles. Finally, we provide the JASPAR2016 R/Bioconductor data package with the data of this release.", "date": "2016-01-01T00:00:00Z", "citationCount": 717, "authors": [ { "name": "Mathelier A." }, { "name": "Fornes O." }, { "name": "Arenillas D.J." }, { "name": "Chen C.-Y." }, { "name": "Denay G." }, { "name": "Lee J." }, { "name": "Shi W." }, { "name": "Shyr C." }, { "name": "Tan G." }, { "name": "Worsley-Hunt R." }, { "name": "Zhang A.W." }, { "name": "Parcy F." }, { "name": "Lenhard B." }, { "name": "Sandelin A." }, { "name": "Wasserman W.W." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkt997", "pmid": "24194598", "pmcid": null, "type": [ "Primary" ], "version": "5.0_ALPHA", "note": null, "metadata": { "title": "JASPAR 2014: An extensively expanded and updated open-access database of transcription factor binding profiles", "abstract": "JASPAR (http://jaspar.genereg.net) is the largest open-access database of matrix-based nucleotide profiles describing the binding preference of transcription factors from multiple species. The fifth major release greatly expands the heart of JASPAR - the JASPAR CORE subcollection, which contains curated, non-redundant profiles - with 135 new curated profiles (74 in vertebrates, 8 in Drosophila melanogaster, 10 in Caenorhabditis elegans and 43 in Arabidopsis thaliana; a 30% increase in total) and 43 older updated profiles (36 in vertebrates, 3 in D. melanogaster and 4 in A. thaliana; a 9% update in total). The new and updated profiles are mainly derived from published chromatin immunoprecipitation-seq experimental datasets. In addition, the web interface has been enhanced with advanced capabilities in browsing, searching and subsetting. Finally, the new JASPAR release is accompanied by a new BioPython package, a new R tool package and a new R/Bioconductor data package to facilitate access for both manual and automated methods. © 2013 The Author(s). Published by Oxford University Press.", "date": "2014-01-01T00:00:00Z", "citationCount": 789, "authors": [ { "name": "Mathelier A." }, { "name": "Zhao X." }, { "name": "Zhang A.W." }, { "name": "Parcy F." }, { "name": "Worsley-Hunt R." }, { "name": "Arenillas D.J." }, { "name": "Buchman S." }, { "name": "Chen C.-Y." }, { "name": "Chou A." }, { "name": "Ienasescu H." }, { "name": "Lim J." }, { "name": "Shyr C." }, { "name": "Tan G." }, { "name": "Zhou M." }, { "name": "Lenhard B." }, { "name": "Sandelin A." }, { "name": "Wasserman W.W." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkp950", "pmid": "19906716", "pmcid": null, "type": [ "Primary" ], "version": "4", "note": null, "metadata": { "title": "JASPAR 2010: The greatly expanded open-access database of transcription factor binding profiles", "abstract": "JASPAR (http://jaspar.genereg.net) is the leading open-access database of matrix profiles describing the DNA-binding patterns of transcription factors (TFs) and other proteins interacting with DNA in a sequence-specific manner. Its fourth major release is the largest expansion of the core database to date: the database now holds 457 non-redundant, curated profiles. The new entries include the first batch of profiles derived from ChIP-seq and ChIP-chip whole-genome binding experiments, and 177 yeast TF binding profiles. The introduction of a yeast division brings the convenience of JASPAR to an active research community. As binding models are refined by newer data, the JASPAR database now uses versioning of matrices: in this release, 12% of the older models were updated to improved versions. Classification of TF families has been improved by adopting a new DNA-binding domain nomenclature. A curated catalog of mammalian TFs is provided, extending the use of the JASPAR profiles to additional TFs belonging to the same structural family. The changes in the database set the system ready for more rapid acquisition of new high-throughput data sources. Additionally, three new special collections provide matrix profile data produced by recent alternative high-throughput approaches. © The Author(s) 2009. Published by Oxford University Press.", "date": "2009-11-10T00:00:00Z", "citationCount": 478, "authors": [ { "name": "Portales-Casamar E." }, { "name": "Thongjuea S." }, { "name": "Kwon A.T." }, { "name": "Arenillas D." }, { "name": "Zhao X." }, { "name": "Valen E." }, { "name": "Yusuf D." }, { "name": "Lenhard B." }, { "name": "Wasserman W.W." }, { "name": "Sandelin A." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkm955", "pmid": "18006571", "pmcid": null, "type": [ "Primary" ], "version": "3", "note": null, "metadata": { "title": "JASPAR, the open access database of transcription factor-binding profiles: New content and tools in the 2008 update", "abstract": "JASPAR is a popular open-access database for matrix models describing DNA-binding preferences for transcription factors and other DNA patterns. With its third major release, JASPAR has been expanded and equipped with additional functions aimed at both casual and power users. The heart of the JASPAR database - the JASPAR CORE sub-database - has increased by 12% in size, and three new specialized sub-databases have been added. New functions include clustering of matrix models by similarity, generation of random matrices by sampling from selected sets of existing models and a language-independent Web Service applications programming interface for matrix retrieval. JASPAR is available at http://jaspar.genereg.net. © 2007 The Author(s).", "date": "2008-01-01T00:00:00Z", "citationCount": 550, "authors": [ { "name": "Bryne J.C." }, { "name": "Valen E." }, { "name": "Tang M.-H.E." }, { "name": "Marstrand T." }, { "name": "Winther O." }, { "name": "Da piedade I." }, { "name": "Krogh A." }, { "name": "Lenhard B." }, { "name": "Sandelin A." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkj115", "pmid": "16381983", "pmcid": null, "type": [ "Primary" ], "version": "2", "note": null, "metadata": null }, { "doi": "10.1093/nar/gkh012", "pmid": "14681366", "pmcid": null, "type": [ "Primary" ], "version": "1", "note": null, "metadata": null } ], "credit": [ { "name": "Albin Sandelin", "email": "albin@binf.ku.dk", "url": "https://albinsandelin.wixsite.com/sandelinlab", "orcidid": "http://orcid.org/0000-0002-7109-7378", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Boris Lenhard", "email": "b.lenhard@imperial.ac.uk", "url": "https://lms.mrc.ac.uk/research-group/computational-regulatory-genomics/", "orcidid": "http://orcid.org/0000-0002-1114-1509", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Wyeth Wasserman", "email": "wyeth@cmmt.ubc.ca", "url": "https://cmmt.ubc.ca/wasserman-lab/", "orcidid": "http://orcid.org/0000-0001-6098-6412", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "François Parcy", "email": "francois.parcy@cea.fr", "url": "https://www.lpcv.fr/en/Pages/Flo_Re/Presentation.aspx", "orcidid": "https://orcid.org/0000-0003-2191-500X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Anthony Mathelier", "email": "anthony.mathelier@ncmm.uio.no", "url": 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