count: 370
list:
- accessibility: null
  additionDate: '2016-05-24T10:51:12Z'
  biotoolsCURIE: biotools:ribogalaxy
  biotoolsID: ribogalaxy
  collectionID: []
  community: null
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: info@sfi.ie
    fundrefid: null
    gridid: null
    name: Science Foundation Ireland
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: ucc.ie
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: http://www.ucc.ie
  - email: ribogalaxy@gmail.com
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://ribogalaxy.ucc.ie/
  - email: p.baranov@ucc.ie
    fundrefid: null
    gridid: null
    name: Pavel V. Baranov
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  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.
  documentation:
  - note: null
    type:
    - Terms of use
    url: http://ribogalaxy.ucc.ie/static/conditions_of_use.html
  - note: null
    type:
    - General
    url: http://ribogalaxy.ucc.ie/
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity:
  - Galaxy
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Raw sequence
        uri: http://edamontology.org/data_0848
      format:
      - term: FASTQ-sanger
        uri: http://edamontology.org/format_1932
    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.
    operation:
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    - term: Alignment
      uri: http://edamontology.org/operation_2928
    - term: Gene expression profiling
      uri: http://edamontology.org/operation_0314
    - term: Gene expression analysis
      uri: http://edamontology.org/operation_2495
    output:
    - data:
        term: Image
        uri: http://edamontology.org/data_2968
      format:
      - term: PNG
        uri: http://edamontology.org/format_3603
    - data:
        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format:
      - term: BAM
        uri: http://edamontology.org/format_2572
      - term: bigWig
        uri: http://edamontology.org/format_3006
    - data:
        term: Sequence image
        uri: http://edamontology.org/data_2969
      format:
      - term: PNG
        uri: http://edamontology.org/format_3603
  homepage: http://ribogalaxy.ucc.ie
  homepage_status: 0
  language: []
  lastUpdate: '2024-02-23T09:02:01.891026Z'
  license: null
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/riboseqorg/RiboGalaxy
  maturity: Mature
  name: RiboGalaxy
  operatingSystem:
  - Windows
  - Mac
  otherID: []
  owner: A.Michel@ucc.ie
  publication:
  - doi: 10.1080/15476286.2016.1141862
    metadata:
      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.
      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.
      citationCount: 67
      date: '2016-03-03T00:00:00Z'
      journal: RNA Biology
      title: 'RiboGalaxy: A browser based platform for the alignment, analysis and
        visualization of ribosome profiling data'
    note: null
    pmcid: PMC4829337
    pmid: '26821742'
    type:
    - Primary
    version: null
  - doi: 10.1016/J.JMB.2023.168043
    metadata:
      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.
      authors:
      - name: Fedorova A.D.
      - name: Tierney J.A.S.
      - name: Michel A.M.
      - name: Baranov P.V.
      citationCount: 1
      date: '2023-07-15T00:00:00Z'
      journal: Journal of Molecular Biology
      title: 'RiboGalaxy: A Galaxy-based Web Platform for Ribosome Profiling Data
        Processing – 2023 Update'
    note: null
    pmcid: null
    pmid: '37356899'
    type:
    - Review
    version: null
  relation: []
  toolType:
  - Workbench
  topic:
  - term: Gene expression
    uri: http://edamontology.org/topic_0203
  validated: 1
  version:
  - '1'
- accessibility: null
  additionDate: '2016-11-28T10:07:17Z'
  biotoolsCURIE: biotools:integron_finder
  biotoolsID: integron_finder
  collectionID:
  - GEM Pasteur
  community: null
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: 10.13039/501100003762
    gridid: grid.428999.7
    name: Institut Pasteur
    note: null
    orcidid: null
    rorid: 0495fxg12
    typeEntity: Institute
    typeRole:
    - Provider
    url: http://www.pasteur.fr/en
  - email: null
    fundrefid: null
    gridid: null
    name: C3BI
    note: null
    orcidid: null
    rorid: null
    typeEntity: Division
    typeRole: []
    url: https://research.pasteur.fr/en/center/c3bi/
  - email: null
    fundrefid: null
    gridid: null
    name: ERC EVOMOBILOME
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: https://erc.europa.eu/projects-and-results/erc-funded-projects/evomobilome
  - email: jean.cury@normalesup.org
    fundrefid: null
    gridid: null
    name: Jean Cury
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Support
    url: null
  - email: bneron@pasteur.fr
    fundrefid: null
    gridid: null
    name: Bertrand Neron
    note: null
    orcidid: https://orcid.org/0000-0002-0220-0482
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: eduardo.rocha@pasteur.fr
    fundrefid: null
    gridid: null
    name: Eduardo Rocha
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Support
    url: https://research.pasteur.fr/fr/member/eduardo-rocha/
  - email: null
    fundrefid: null
    gridid: null
    name: Microbial Evolutionary Genomics
    note: CNRS - UMR 352
    orcidid: null
    rorid: null
    typeEntity: Division
    typeRole: []
    url: https://research.pasteur.fr/en/team/microbial-evolutionary-genomics/
  - email: jean.cury@normalesup.org
    fundrefid: null
    gridid: null
    name: Jean Cury
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: bneron@pasteur.fr
    fundrefid: null
    gridid: null
    name: Bertrand Neron
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: eduardo.rocha@pasteur.fr
    fundrefid: null
    gridid: null
    name: Eduardo Rocha
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://research.pasteur.fr/fr/member/eduardo-rocha/
  - email: eloi.littner@pasteur.fr
    fundrefid: null
    gridid: null
    name: Eloi Littner
    note: null
    orcidid: https://orcid.org/0000-0002-8793-9584
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Matthieu Haudiquet
    note: null
    orcidid: https://orcid.org/0000-0002-0878-2209
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Amandine PERRIN
    note: null
    orcidid: https://orcid.org/0000-0003-4797-6185
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: INCEPTION
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: https://anr.fr/ProjetIA-16-CONV-0005
  - email: null
    fundrefid: null
    gridid: null
    name: Laboratoire d’Excellence IBEID Integrative Biology of Emerging Infectious
      Diseases
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: https://anr.fr/ProjetIA-10-LABX-0062
  description: A tool to detect Integron in DNA sequences.
  documentation:
  - note: null
    type:
    - General
    url: http://integronfinder.readthedocs.org/
  download: []
  editPermission:
    authors:
    - hmenager
    - khillion
    - bneron
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: DNA sequence (raw)
        uri: http://edamontology.org/data_3497
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: Single fasta file
    operation:
    - term: Nucleic acid feature detection
      uri: http://edamontology.org/operation_0415
    - term: Sequence motif recognition
      uri: http://edamontology.org/operation_0239
    - term: Protein feature detection
      uri: http://edamontology.org/operation_3092
    - term: Genome annotation
      uri: http://edamontology.org/operation_0362
    output:
    - data:
        term: Sequence record
        uri: http://edamontology.org/data_0849
      format:
      - term: GenBank format
        uri: http://edamontology.org/format_1936
    - data:
        term: Feature table
        uri: http://edamontology.org/data_1270
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
  homepage: https://github.com/gem-pasteur/Integron_Finder
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2024-02-14T13:27:58.376472Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/gem-pasteur/Integron_Finder/
  maturity: Mature
  name: Integron Finder
  operatingSystem:
  - Linux
  - Mac
  otherID: []
  owner: jeanrjc
  publication:
  - doi: 10.1093/nar/gkw319
    metadata:
      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.
      authors:
      - name: Cury J.
      - name: Jove T.
      - name: Touchon M.
      - name: Neron B.
      - name: Rocha E.P.
      citationCount: 186
      date: '2016-06-02T00:00:00Z'
      journal: Nucleic Acids Research
      title: Identification and analysis of integrons and cassette arrays in bacterial
        genomes
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: 1.5.1
  - doi: 10.3390/microorganisms10020224
    metadata:
      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.
      authors:
      - name: Fonseca E.L.
      - name: Vicente A.C.
      citationCount: 9
      date: '2022-02-01T00:00:00Z'
      journal: Microorganisms
      title: 'Integron Functionality and Genome Innovation: An Update on the Subtle
        and Smart Strategy of Integrase and Gene Cassette Expression Regulation'
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: 2.0.1
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Functional genomics
    uri: http://edamontology.org/topic_0085
  - term: Mobile genetic elements
    uri: http://edamontology.org/topic_0798
  - term: Molecular biology
    uri: http://edamontology.org/topic_3047
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  validated: 1
  version:
  - 1.5.1
  - 2.0.1
  - 2.0.2
  - 2.0.3
- accessibility: Open access
  additionDate: '2023-12-13T14:54:35.138186Z'
  biotoolsCURIE: biotools:altair
  biotoolsID: altair
  collectionID:
  - COVID-19
  - Rare Disease
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: jorge.miguel.ferreira.silva@ua.pt
    fundrefid: null
    gridid: null
    name: Jorge M. Silva
    note: Researcher at IEETA. J.M.S. has received funding from the EC under grant
      agreement 101081813, Genomic Data Infrastructure.
    orcidid: http://orcid.org/0000-0002-6331-6091
    rorid: null
    typeEntity: Project
    typeRole:
    - Contributor
    url: null
  - email: pratas@ua.pt
    fundrefid: null
    gridid: null
    name: Diogo Pratas
    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.
    orcidid: http://orcid.org/0000-0003-1176-552X
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: null
  description: 'AltaiR is a C toolkit for alignment-free and spatial-temporal analysis
    of multi-FASTA data.


    This 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.'
  documentation: []
  download: []
  editPermission:
    authors:
    - pratas
    type: group
  elixirCommunity: []
  elixirNode:
  - Portugal
  elixirPlatform:
  - Tools
  - Data
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Sequence analysis
      uri: http://edamontology.org/operation_2403
    output: []
  homepage: https://github.com/cobilab/altair
  homepage_status: 0
  language:
  - C
  lastUpdate: '2023-12-13T14:54:35.146893Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/cobilab/altair
  maturity: Mature
  name: AltaiR
  operatingSystem:
  - Linux
  otherID: []
  owner: jorgeMFS
  publication: []
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  - term: Computational biology
    uri: http://edamontology.org/topic_3307
  - term: Transcriptomics
    uri: http://edamontology.org/topic_3308
  - term: Medicine
    uri: http://edamontology.org/topic_3303
  validated: 0
  version:
  - 1.0.1
- accessibility: null
  additionDate: '2016-04-21T06:14:09Z'
  biotoolsCURIE: biotools:mrbayes
  biotoolsID: mrbayes
  collectionID: []
  community: null
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Fredrik Ronquist
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Paul van der Mark
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Maxim Teslenko
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Donald Simon
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: John Huelsenbeck
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Bret Larget
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Chi Zhang
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Dept. of Biodiversity Informatics at the Swedish Museum of Natural History
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Vetenskapsrådet
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
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    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: NSF
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
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    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: NIH
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
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    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: icm.uu.se
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
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    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://nbisweden.github.io/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.
  documentation:
  - note: null
    type:
    - Terms of use
    url: https://github.com/NBISweden/MrBayes/blob/develop/COPYING
  - note: null
    type:
    - General
    url: http://nbisweden.github.io/MrBayes/
  download:
  - note: null
    type: Source code
    url: https://github.com/NBISweden/MrBayes/releases/tag/v3.2.6
    version: null
  - note: null
    type: Binaries
    url: https://github.com/NBISweden/MrBayes/releases/tag/v3.2.6
    version: null
  editPermission:
    authors:
    - sergitobara
    - EngyNasr
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  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Phylogenetic tree generation (maximum likelihood and Bayesian methods)
      uri: http://edamontology.org/operation_0547
    output: []
  homepage: http://nbisweden.github.io/MrBayes/
  homepage_status: 0
  language:
  - C
  lastUpdate: '2023-11-03T08:32:13.053903Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/NBISweden/MrBayes
  maturity: Mature
  name: MrBayes
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: andreas.kahari@icm.uu.se
  publication:
  - doi: 10.1093/bioinformatics/17.8.754
    metadata:
      abstract: 'Summary: The program MRBAYES performs Bayesian inference of phylogeny
        using a variant of Markov chain Monte Carlo.'
      authors:
      - name: Huelsenbeck J.P.
      - name: Ronquist F.
      citationCount: 18632
      date: '2001-01-01T00:00:00Z'
      journal: Bioinformatics
      title: 'MRBAYES: Bayesian inference of phylogenetic trees'
    note: null
    pmcid: null
    pmid: '11524383'
    type:
    - Primary
    version: null
  - doi: 10.1093/bioinformatics/btg180
    metadata:
      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.'
      authors:
      - name: Ronquist F.
      - name: Huelsenbeck J.P.
      citationCount: 24269
      date: '2003-08-12T00:00:00Z'
      journal: Bioinformatics
      title: 'MrBayes 3: Bayesian phylogenetic inference under mixed models'
    note: null
    pmcid: null
    pmid: '12912839'
    type: []
    version: '3'
  - doi: 10.1093/sysbio/sys029
    metadata:
      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).
      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.
      citationCount: 15381
      date: '2012-05-01T00:00:00Z'
      journal: Systematic Biology
      title: 'Mrbayes 3.2: Efficient bayesian phylogenetic inference and model choice
        across a large model space'
    note: null
    pmcid: PMC3329765
    pmid: '22357727'
    type: []
    version: '3.2'
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Phylogenetics
    uri: http://edamontology.org/topic_3293
  validated: 1
  version:
  - 3.2.6
- accessibility: Open access
  additionDate: '2017-04-21T12:12:16Z'
  biotoolsCURIE: biotools:clustal2
  biotoolsID: clustal2
  collectionID:
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  - Bioconda
  - galaxyPasteur
  - DebianMed
  community: null
  confidence_flag: null
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  credit:
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    note: null
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    rorid: null
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    typeRole:
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    url: null
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    fundrefid: null
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    name: Science Foundation Ireland
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole: []
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  description: 'Multiple sequence alignment program with a command-line interface
    (Clustal W) and a graphical user interface (Clustal X). The display colours allow
    conserved features to be highlighted for easy viewing in the alignment. It is
    available for several platforms, including Windows, Macintosh PowerMac, Linux
    and Solaris.

    Names occassionally spelled also as Clustal W2, ClustalW2, ClustalW, ClustalX,
    Clustal2.'
  documentation:
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    type:
    - General
    url: http://www.clustal.org/clustal2/#Documentation
  download:
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    type: Downloads page
    url: http://www.clustal.org/clustal2/#Download
    version: null
  - note: Debian package (Debian Med Packaging Team). Source code package of the command-line
      interface Clustal W and the corresponding binary package.
    type: Software package
    url: https://tracker.debian.org/pkg/clustalw
    version: null
  - note: Debian package (Debian Med Packaging Team). Source code package of the graphical
      user interface Clustal X and the corresponding binary package.
    type: Software package
    url: https://tracker.debian.org/pkg/clustalx
    version: null
  - note: Conda package (Bioconda channel) of the command-line interface Clustal W.
      Conda recipe at https://github.com/bioconda/bioconda-recipes/tree/master/recipes/clustalw/meta.yaml
    type: Software package
    url: https://bioconda.github.io/recipes/clustalw/README.html
    version: null
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  function:
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    input:
    - data:
        term: Sequence
        uri: http://edamontology.org/data_2044
      format:
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        uri: http://edamontology.org/format_1929
    note: null
    operation:
    - term: Multiple sequence alignment
      uri: http://edamontology.org/operation_0492
    output:
    - data:
        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
  homepage: http://www.clustal.org/clustal2/
  homepage_status: 0
  language: []
  lastUpdate: '2023-11-02T09:45:49.842067Z'
  license: LGPL-3.0
  link:
  - note: null
    type:
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    url: https://galaxy.pasteur.fr/?tool_id=clustalw&version=0.1&__identifer=058xsts0d9se
  - note: null
    type:
    - Issue tracker
    url: http://bioinf.ucd.ie/bugzilla/buglist.cgi?quicksearch=clustal
  maturity: Mature
  name: Clustal 2 (Clustal W, Clustal X)
  operatingSystem:
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  - Windows
  - Mac
  otherID:
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    value: RRID:SCR_002909
    version: null
  - type: rrid
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    version: null
  owner: jison
  publication:
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    metadata: null
    note: Historical publication on CLUSTAL W. Open access to PDF only.
    pmcid: PMC308517
    pmid: null
    type:
    - Primary
    version: historical CLUSTAL W
  - doi: 10.1093/nar/25.24.4876
    metadata: null
    note: Historical publication on CLUSTAL X. Open access.
    pmcid: PMC147148
    pmid: null
    type:
    - Primary
    version: historical CLUSTAL X
  - doi: 10.1093/bioinformatics/btm404
    metadata: null
    note: Publication on Clustal 2 (Clustal W and Clustal X). Closed access.
    pmcid: null
    pmid: null
    type:
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    version: '2.0'
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    metadata: null
    note: Historical publication on CLUSTAL. Closed access.
    pmcid: null
    pmid: null
    type:
    - Other
    version: historical CLUSTAL
  relation:
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    type: isNewVersionOf
  toolType:
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  - Desktop application
  topic:
  - term: Phylogeny
    uri: http://edamontology.org/topic_0084
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  validated: 0
  version:
  - 2.0 - 2.1
- accessibility: Open access
  additionDate: '2018-11-20T06:38:59Z'
  biotoolsCURIE: biotools:galaxy_australia
  biotoolsID: galaxy_australia
  collectionID: []
  community: null
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: ARDC
    note: Galaxy Australia receives investment from Australian Research Data Commons
      (ARDC). The ARDC is funded by the National Collaborative Research Infrastructure
      Strategy (NCRIS).
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Primary contact
    url: https://ardc.edu.au/
  - email: null
    fundrefid: null
    gridid: null
    name: Bioplatforms Australia
    note: Galaxy Australia receives investment from Bioplatforms Australia. Bioplatforms
      Australia is funded by the National Collaborative Research Infrastructure Strategy
      (NCRIS).
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole: []
    url: https://bioplatforms.com/
  - email: null
    fundrefid: null
    gridid: null
    name: Queensland Government - RICF scheme
    note: Galaxy Australia received investment from the Queensland Government - RICF
      scheme from 2019-2023
    orcidid: null
    rorid: null
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    typeRole: []
    url: https://science.des.qld.gov.au/funding/ricf
  - email: null
    fundrefid: null
    gridid: null
    name: QCIF
    note: Staff based at QCIF manage the Galaxy Australia service. Some of these staff
      are part funded by QCIF sourced funds.
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
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    url: https://www.qcif.edu.au/
  - email: null
    fundrefid: null
    gridid: null
    name: Melbourne Bioinformatics
    note: Staff based at Melbourne Bioinformatics manage the Galaxy Australia service.
      Some of these staff are part funded by the University of Melbourne.
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
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    url: https://www.melbournebioinformatics.org.au/
  - email: null
    fundrefid: null
    gridid: null
    name: Australian BioCommons
    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.
    orcidid: null
    rorid: null
    typeEntity: Project
    typeRole: []
    url: https://www.biocommons.org.au/
  description: 'Galaxy Australia is a hosted instance of the Galaxy web-based platform
    for data intensive biological research, for all Australian researchers.

    In addition to being accessible through a web interface, Galaxy Australia can
    also be accessed programmatically, through shell scripts and other programs via
    an API'
  documentation:
  - note: Galaxy Australia uses the standard Galaxy API.
    type:
    - API documentation
    url: https://galaxyproject.org/develop/api/
  - note: Galaxy Australia Data Policy
    type:
    - Terms of use
    url: https://usegalaxy-au.github.io/galaxy/data-policy.html
  download: []
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  function:
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    input: []
    note: null
    operation:
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      uri: http://edamontology.org/operation_2945
    - term: Data handling
      uri: http://edamontology.org/operation_2409
    output: []
  homepage: https://usegalaxy.org.au
  homepage_status: 0
  language: []
  lastUpdate: '2023-09-26T22:49:04.577938Z'
  license: null
  link: []
  maturity: Mature
  name: Galaxy Australia
  operatingSystem: []
  otherID: []
  owner: jchrist
  publication:
  - doi: 10.1093/nar/gkaa434
    metadata:
      abstract: 'Galaxy (https://galaxyproject.org) is a web-based computational workbench
        used by tens of thousands of scientists across the world to analyze large
        biomedical datasets. 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. New
        community resources include large public servers in Europe and Australia,
        an increasing number of regional and local Galaxy communities, and substantial
        growth in the Galaxy Training Network.'
      authors:
      - name: Jalili V.
      - name: Afgan E.
      - name: Gu Q.
      - name: Clements D.
      - name: Blankenberg D.
      - name: Goecks J.
      - name: Taylor J.
      - name: Nekrutenko A.
      citationCount: 214
      date: '2021-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'The Galaxy platform for accessible, reproducible and collaborative biomedical
        analyses: 2020 update'
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType:
  - Workbench
  - Web application
  - Web API
  topic:
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  validated: 1
  version: []
- accessibility: null
  additionDate: '2016-08-13T19:15:03Z'
  biotoolsCURIE: biotools:grnsight
  biotoolsID: grnsight
  collectionID: []
  community: null
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  cost: Free of charge
  credit:
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    name: Ona O. Igbinedion
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    typeRole:
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    url: null
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    note: null
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    typeEntity: Person
    typeRole:
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    url: null
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    fundrefid: null
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    name: Ian M. Green
    note: null
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    fundrefid: null
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    note: null
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    name: John L. Lopez
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    fundrefid: null
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    name: NSF award 0921038; LMU Rains Research Assistant Program; LMU Summer Undergraduate
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    fundrefid: null
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  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.
  documentation:
  - note: null
    type:
    - General
    url: http://dondi.github.io/GRNsight/documentation.html
  download:
  - note: null
    type: Source code
    url: https://github.com/dondi/GRNsight/archive/master.zip
    version: null
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  function:
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    input: []
    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.
    operation:
    - term: Gene regulatory network analysis
      uri: http://edamontology.org/operation_1781
    - term: Pathway or network visualisation
      uri: http://edamontology.org/operation_3083
    output: []
  homepage: http://dondi.github.io/GRNsight/
  homepage_status: 0
  language:
  - JavaScript
  lastUpdate: '2023-08-29T16:51:15.145002Z'
  license: BSD-3-Clause
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/dondi/GRNsight
  maturity: Mature
  name: GRNsight
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: dondi@lmu.edu
  publication:
  - doi: 10.7717/peerj-cs.85
    metadata:
      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.
      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.
      citationCount: 2
      date: '2016-01-01T00:00:00Z'
      journal: PeerJ Computer Science
      title: 'GRNsight: A web application and service for visualizing models of small-to
        medium-scale gene regulatory networks'
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  - doi: 10.5281/zenodo.7411630
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Other
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  - term: Gene regulation
    uri: http://edamontology.org/topic_0204
  validated: 1
  version:
  - 6.0.7
- accessibility: Open access
  additionDate: '2021-02-18T12:08:51Z'
  biotoolsCURIE: biotools:carveme
  biotoolsID: carveme
  collectionID:
  - ELIXIR-NO
  - ELIXIR-Norway
  - NTNU tools
  community: null
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Daniel Machado
    note: null
    orcidid: https://orcid.org/0000-0002-2063-5383
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    - Developer
    - Documentor
    - Maintainer
    url: null
  - email: support@elixir.no
    fundrefid: null
    gridid: null
    name: The Norwegian Bioinformatics Platform (ELIXIR-Norway) Helpdesk
    note: null
    orcidid: null
    rorid: null
    typeEntity: Consortium
    typeRole:
    - Support
    url: https://elixir.no/helpdesk
  - email: null
    fundrefid: null
    gridid: null
    name: Sergej Andrejev
    note: null
    orcidid: https://orcid.org/0000-0002-7875-0261
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Melanie Tramontano
    note: null
    orcidid: https://orcid.org/0000-0001-6407-527X
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Kiran Raosaheb Patil
    note: null
    orcidid: https://orcid.org/0000-0002-6166-8640
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: grid.5947.f
    name: NTNU
    note: Developed at NTNU 2020-present
    orcidid: null
    rorid: 05xg72x27
    typeEntity: Institute
    typeRole:
    - Provider
    url: http://www.ntnu.edu
  - email: null
    fundrefid: null
    gridid: grid.4709.a
    name: European Molecular Biology Laboratory (EMBL)
    note: Developed at EMBL 2017-2019
    orcidid: null
    rorid: 03mstc592
    typeEntity: Institute
    typeRole:
    - Provider
    url: http://embl.org/
  - email: null
    fundrefid: null
    gridid: null
    name: European Union's Horizon 2020
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole: []
    url: https://doi.org/10.3030/686070
  - email: erin.calhoun@uit.no
    fundrefid: null
    gridid: null
    name: Erin Calhoun
    note: Curation of bio.tools profile - contact me with updates/corrections.
    orcidid: https://orcid.org/0009-0003-3752-7156
    rorid: null
    typeEntity: Person
    typeRole:
    - Documentor
    url: null
  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. During
    the model carving process, users can select from provided templates or create
    their own customized universe model to suit their specific needs.
  documentation:
  - note: null
    type:
    - General
    - Installation instructions
    - Quick start guide
    - Command-line options
    - User manual
    url: https://carveme.readthedocs.io/en/latest/index.html
  - note: null
    type:
    - Citation instructions
    url: https://github.com/cdanielmachado/carveme#readme
  - note: null
    type:
    - Release notes
    url: https://github.com/cdanielmachado/carveme/releases
  download:
  - note: Latest release as of 3 August 2023
    type: Source code
    url: https://github.com/cdanielmachado/carveme/releases/tag/1.5.2
    version: 1.5.2
  - note: null
    type: Source code
    url: https://github.com/cdanielmachado/carveme/releases
    version: All
  editPermission:
    authors:
    - eca008
    type: group
  elixirCommunity:
  - Marine Metagenomics
  - Metabolomics
  - Microbial Biotechnology
  - Proteomics
  elixirNode:
  - Norway
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence
        uri: http://edamontology.org/data_2976
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: DNA sequence
        uri: http://edamontology.org/data_3494
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: NCBI genome accession
        uri: http://edamontology.org/data_2787
      format: []
    note: Homology-based search is default using diamond. Orthology-based search can
      be performed with eggNOG-mapper (kegg-bigg branch).
    operation:
    - term: Metabolic network modelling
      uri: http://edamontology.org/operation_3660
    - term: Homology-based gene prediction
      uri: http://edamontology.org/operation_3663
    output:
    - data:
        term: Pathway or network report
        uri: http://edamontology.org/data_2984
      format:
      - term: XML
        uri: http://edamontology.org/format_2332
      - term: SBML
        uri: http://edamontology.org/format_2585
  - cmd: null
    input:
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        term: Protein sequence
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      format:
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        uri: http://edamontology.org/format_1929
    - data:
        term: DNA sequence
        uri: http://edamontology.org/data_3494
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: NCBI genome accession
        uri: http://edamontology.org/data_2787
      format: []
    - data:
        term: Pathway or network report
        uri: http://edamontology.org/data_2984
      format:
      - term: XML
        uri: http://edamontology.org/format_2332
    - data:
        term: Cultivation parameter
        uri: http://edamontology.org/data_3724
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
      - term: TSV
        uri: http://edamontology.org/format_3475
    note: null
    operation:
    - term: Scaffold gap completion
      uri: http://edamontology.org/operation_3217
    output:
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        term: Pathway or network report
        uri: http://edamontology.org/data_2984
      format:
      - term: XML
        uri: http://edamontology.org/format_2332
      - term: SBML
        uri: http://edamontology.org/format_2585
  - cmd: null
    input:
    - data:
        term: Pathway or network report
        uri: http://edamontology.org/data_2984
      format:
      - term: XML
        uri: http://edamontology.org/format_2332
    note: null
    operation:
    - term: Aggregation
      uri: http://edamontology.org/operation_3436
    output:
    - data:
        term: Pathway or network report
        uri: http://edamontology.org/data_2984
      format:
      - term: SBML
        uri: http://edamontology.org/format_2585
  homepage: https://github.com/cdanielmachado/carveme
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2023-08-15T10:51:32.592010Z'
  license: Apache-2.0
  link:
  - note: null
    type:
    - Repository
    - Issue tracker
    url: https://github.com/cdanielmachado/carveme
  - note: Helpdesk and support for ELIXIR Norway services
    type:
    - Helpdesk
    url: https://elixir.no/helpdesk
  maturity: Mature
  name: CarveMe
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: dmachado
  publication:
  - doi: 10.1093/nar/gky537
    metadata:
      abstract: Genome-scale metabolic models are instrumental in uncovering operating
        principles of cellular metabolism, for model-guided re-engineering, and unraveling
        cross-feeding in microbial communities. 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.
      authors:
      - name: Machado D.
      - name: Andrejev S.
      - name: Tramontano M.
      - name: Patil K.R.
      citationCount: 239
      date: '2018-09-06T00:00:00Z'
      journal: Nucleic Acids Research
      title: Fast automated reconstruction of genome-scale metabolic models for microbial
        species and communities
    note: null
    pmcid: PMC6125623
    pmid: '30192979'
    type:
    - Primary
    version: 1.0.0
  - doi: 10.1038/s41559-022-01939-0
    metadata:
      abstract: ''
      authors:
      - name: Machado D.
      - name: Patil K.R.
      citationCount: 0
      date: '2023-02-01T00:00:00Z'
      journal: Nature Ecology and Evolution
      title: 'Reply to: Erroneous predictions of auxotrophies by CarveMe'
    note: null
    pmcid: null
    pmid: '36471121'
    type:
    - Other
    version: null
  relation:
  - biotoolsID: bigg_models
    type: uses
  - biotoolsID: diamond
    type: uses
  toolType:
  - Command-line tool
  topic:
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  - term: Omics
    uri: http://edamontology.org/topic_3391
  - term: Systems biology
    uri: http://edamontology.org/topic_2259
  - term: Computational biology
    uri: http://edamontology.org/topic_3307
  validated: 0
  version:
  - 1.0.0
  - 1.1.0
  - 1.2.0
  - 1.3.0
  - 1.4.0 - 1.4.1
  - 1.5.0 - 1.5.2
- accessibility: Open access
  additionDate: '2023-08-10T08:23:57.988811Z'
  biotoolsCURIE: biotools:omnipy
  biotoolsID: omnipy
  collectionID:
  - ELIXIR-NO
  - ELIXIR-Norway
  - UiO tools
  community: null
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: sveinugu@gmail.com
    fundrefid: null
    gridid: null
    name: Sveinung Gundersen
    note: null
    orcidid: https://orcid.org/0000-0001-9888-7954
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    - Developer
    - Documentor
    - Maintainer
    - Support
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Pável Vázquez
    note: null
    orcidid: https://orcid.org/0000-0003-0471-9517
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    - Documentor
    - Support
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Federico Bianchini
    note: null
    orcidid: https://orcid.org/0000-0002-9016-4820
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Joshua Baskaran
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Jeanne Cheneby
    note: null
    orcidid: https://orcid.org/0000-0003-4553-3110
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Ahmed Ghanem
    note: null
    orcidid: https://orcid.org/0000-0002-2006-4242
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Eivind Hovig
    note: null
    orcidid: https://orcid.org/0000-0002-9103-1077
    rorid: null
    typeEntity: Person
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: ELIXIR Norway
    note: null
    orcidid: null
    rorid: null
    typeEntity: Consortium
    typeRole:
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    url: https://elixir.no
  - email: null
    fundrefid: 10.13039/501100005366
    gridid: grid.5510.1
    name: University of Oslo
    note: null
    orcidid: null
    rorid: 01xtthb56
    typeEntity: Institute
    typeRole:
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    url: null
  - email: null
    fundrefid: 10.13039/501100005416
    gridid: grid.13985.36
    name: The Research Council of Norway
    note: null
    orcidid: null
    rorid: 00epmv149
    typeEntity: Funding agency
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Gavin Chait
    note: Contributing to Biohackathon projects (Oct-Nov 2023) related to omnipy
    orcidid: https://orcid.org/0000-0003-3733-6299
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Timo Mühlhaus
    note: Contributing to Biohackathon projects (Oct-Nov 2023) related to omnipy
    orcidid: https://orcid.org/0000-0003-3925-6778
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Sebastian Beier
    note: Contributing to Biohackathon projects (Oct-Nov 2023) related to omnipy
    orcidid: https://orcid.org/0000-0002-2177-8781
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Stuart Owen
    note: Contributing to Biohackathon projects (Oct-Nov 2023) related to omnipy
    orcidid: https://orcid.org/0000-0003-2130-0865
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: erin.calhoun@uit.no
    fundrefid: null
    gridid: null
    name: Erin Calhoun
    note: Curation of bio.tools record - please contact me with updates/corrections.
    orcidid: https://orcid.org/0009-0003-3752-7156
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  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.
  documentation:
  - note: null
    type:
    - API documentation
    url: https://omnipy.readthedocs.io/en/latest/
  download:
  - note: Latest release (still under development)
    type: Source code
    url: https://pypi.org/project/omnipy/#files
    version: 0.10.4
  editPermission:
    authors:
    - matus.kalas@uib.no
    - ELIXIR-NO
    - UiO
    - UiT
    type: group
  elixirCommunity:
  - 3D-BioInfo
  - Federated Human Data
  - Human Copy Number Variation
  - Intrinsically Disordered Proteins
  - Marine Metagenomics
  - Metabolomics
  - Microbial Biotechnology
  - Plant Sciences
  - Proteomics
  - Rare Diseases
  elixirNode:
  - Norway
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Data reference
        uri: http://edamontology.org/data_2093
      format:
      - term: Python script
        uri: http://edamontology.org/format_3996
    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.
    operation:
    - term: Data retrieval
      uri: http://edamontology.org/operation_2422
    - term: Service invocation
      uri: http://edamontology.org/operation_3763
    - term: Mapping
      uri: http://edamontology.org/operation_2429
    - term: Filtering
      uri: http://edamontology.org/operation_3695
    - term: Formatting
      uri: http://edamontology.org/operation_0335
    output:
    - data:
        term: Database search results
        uri: http://edamontology.org/data_2080
      format:
      - term: JSON
        uri: http://edamontology.org/format_3464
  - cmd: null
    input:
    - data:
        term: Text data
        uri: http://edamontology.org/data_2526
      format:
      - term: JSON
        uri: http://edamontology.org/format_3464
      - term: TSV
        uri: http://edamontology.org/format_3475
      - term: Binary format
        uri: http://edamontology.org/format_2333
      - term: GSuite
        uri: http://edamontology.org/format_3775
      - term: Textual format
        uri: http://edamontology.org/format_2330
    note: Import data as files in a supported format. Output as pandas DataFrames
      with embedded JSON objects/lists and reference metadata.
    operation:
    - term: Format detection
      uri: http://edamontology.org/operation_3357
    - term: Parsing
      uri: http://edamontology.org/operation_1812
    - term: Formatting
      uri: http://edamontology.org/operation_0335
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    - term: Splitting
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    output:
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      format: []
  - cmd: null
    input:
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        term: Matrix
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      format: []
    note: Data cleanup and transformation.
    operation:
    - term: Standardisation and normalisation
      uri: http://edamontology.org/operation_3435
    output:
    - data:
        term: Matrix
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      format: []
  - cmd: null
    input:
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        term: Matrix
        uri: http://edamontology.org/data_2082
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    note: Manual mapping of FAIRtracks objects and attributes to corresponding tables
      and columns in the original data.
    operation:
    - term: Mapping
      uri: http://edamontology.org/operation_2429
    output:
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        term: Database cross-mapping
        uri: http://edamontology.org/data_0954
      format: []
  - cmd: null
    input:
    - data:
        term: Matrix
        uri: http://edamontology.org/data_2082
      format: []
    - data:
        term: Data reference
        uri: http://edamontology.org/data_2093
      format:
      - term: Matrix format
        uri: http://edamontology.org/format_3033
    - data:
        term: Database cross-mapping
        uri: http://edamontology.org/data_0954
      format: []
    note: Generate initial FAIRtracks tables by applying the model map, mapping FAIRtracks
      attributes with one or more attributes (columns) in the original table.
    operation:
    - term: Aggregation
      uri: http://edamontology.org/operation_3436
    - term: Mapping
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    - term: Service invocation
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    output:
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        uri: http://edamontology.org/data_3509
      format:
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  - cmd: null
    input: []
    note: null
    operation:
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  homepage: https://fairtracks.net/fair/#fair-07-transformation
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2023-08-15T07:24:18.092241Z'
  license: Apache-2.0
  link:
  - note: PyPI page for omnipy
    type:
    - Repository
    url: https://pypi.org/project/omnipy/
  - note: null
    type:
    - Issue tracker
    - Repository
    url: https://github.com/fairtracks/omnipy
  - note: Example projects using the omnipy package
    type:
    - Repository
    url: https://github.com/fairtracks/omnipy_examples
  - note: Omnipy was developed as part of the FAIRtracks project
    type:
    - Service
    url: https://fairtracks.net/
  - note: The Prefect workflow orchestration platform
    type:
    - Other
    url: https://www.prefect.io/
  maturity: Emerging
  name: omnipy
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: eca008
  publication: []
  relation:
  - biotoolsID: pandas
    type: uses
  toolType:
  - Library
  topic:
  - term: Data architecture, analysis and design
    uri: http://edamontology.org/topic_3365
  - term: Data identity and mapping
    uri: http://edamontology.org/topic_3345
  - term: Data integration and warehousing
    uri: http://edamontology.org/topic_3366
  - term: Data mining
    uri: http://edamontology.org/topic_3473
  - term: Data quality management
    uri: http://edamontology.org/topic_3572
  - term: Data submission, annotation and curation
    uri: http://edamontology.org/topic_0219
  - term: Ontology and terminology
    uri: http://edamontology.org/topic_0089
  - term: Workflows
    uri: http://edamontology.org/topic_0769
  validated: 0
  version:
  - 0.10.4
- accessibility: Open access
  additionDate: '2015-03-18T11:02:08Z'
  biotoolsCURIE: biotools:jaspar
  biotoolsID: jaspar
  collectionID:
  - ELIXIR-NO
  - ELIXIR-Norway
  - JASPAR
  community: null
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  cost: Free of charge
  credit:
  - email: albin@binf.ku.dk
    fundrefid: null
    gridid: null
    name: Albin Sandelin
    note: null
    orcidid: http://orcid.org/0000-0002-7109-7378
    rorid: null
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    typeRole:
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    url: https://albinsandelin.wixsite.com/sandelinlab
  - email: b.lenhard@imperial.ac.uk
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    note: null
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    rorid: null
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    url: https://lms.mrc.ac.uk/research-group/computational-regulatory-genomics/
  - email: wyeth@cmmt.ubc.ca
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    name: Wyeth Wasserman
    note: null
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    rorid: null
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    typeRole:
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    url: https://cmmt.ubc.ca/wasserman-lab/
  - email: francois.parcy@cea.fr
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    name: François Parcy
    note: null
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    rorid: null
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    typeRole:
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    url: https://www.lpcv.fr/en/Pages/Flo_Re/Presentation.aspx
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    note: null
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    rorid: null
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    typeRole:
    - Primary contact
    url: https://mathelierlab.com/
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    fundrefid: null
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    note: Helpdesk and support for ELIXIR Norway services
    orcidid: null
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    typeRole:
    - Support
    url: https://elixir.no/helpdesk
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    fundrefid: null
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    name: Alejandro Aguirre
    note: null
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    typeRole:
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    url: null
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    fundrefid: null
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    name: Benoit Ballester
    note: null
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    url: null
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    typeRole:
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    - Maintainer
    - Support
    url: null
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    name: Jaime A Castro-Mondragon
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    - Maintainer
    - Support
    url: null
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    name: Roza Berhanu Lemma
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    fundrefid: null
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    name: Tiffany Y Leung
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    name: Jérémy Lucas
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    name: Nicolás Manosalva Pérez
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    fundrefid: null
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    name: Ieva Rauluseviciute
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    name: Rafael Riudavets-Puig
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    - Contributor
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    fundrefid: null
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    name: Daniel Schmelter
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    fundrefid: null
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    name: Laura Turchi
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    - Contributor
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    fundrefid: null
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    name: Klaas Vandepoele
    note: null
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    - Contributor
    url: null
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    fundrefid: 10.13039/501100005416
    gridid: grid.13985.36
    name: The Research Council of Norway
    note: null
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    rorid: 00epmv149
    typeEntity: Funding agency
    typeRole: []
    url: http://www.forskningsradet.no/en/Home_page/1177315753906
  - email: erin.calhoun@uit.no
    fundrefid: null
    gridid: null
    name: Erin Calhoun
    note: Curation for bio.tools profile - please contact me with updates/corrections
    orcidid: https://orcid.org/0009-0003-3752-7156
    rorid: null
    typeEntity: Person
    typeRole:
    - Documentor
    url: null
  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.
  documentation:
  - note: null
    type:
    - General
    - Governance
    url: http://jaspar.genereg.net/docs/
  - note: null
    type:
    - FAQ
    url: http://jaspar.genereg.net/faq/
  - note: null
    type:
    - API documentation
    url: http://jaspar.genereg.net/api/v1/docs/
  - note: Documentation for pyJASPAR
    type:
    - Citation instructions
    - Command-line options
    - Installation instructions
    - User manual
    url: https://pyjaspar.readthedocs.io/en/latest/
  - note: Documentation for the Bioconductor package
    type:
    - Command-line options
    - User manual
    url: https://bioconductor.org/packages/release/data/annotation/vignettes/JASPAR2022/inst/doc/JASPAR2022.html
  download:
  - note: null
    type: Downloads page
    url: http://jaspar.genereg.net/downloads/
    version: null
  - note: null
    type: API specification
    url: https://jaspar.genereg.net/api/
    version: null
  - note: Repository for pyJASPAR
    type: Source code
    url: https://github.com/asntech/pyjaspar
    version: null
  editPermission:
    authors:
    - eca008
    type: group
  elixirCommunity:
  - Federated Human Data
  - Plant Sciences
  elixirNode:
  - Norway
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Transcription factor name
        uri: http://edamontology.org/data_2755
      format: []
    - data:
        term: Transcription factor identifier
        uri: http://edamontology.org/data_1077
      format: []
    - data:
        term: Taxon
        uri: http://edamontology.org/data_1868
      format: []
    - data:
        term: Family name
        uri: http://edamontology.org/data_2732
      format: []
    - data:
        term: Species name
        uri: http://edamontology.org/data_1045
      format: []
    - data:
        term: UniProt ID
        uri: http://edamontology.org/data_2291
      format: []
    - data:
        term: Text
        uri: http://edamontology.org/data_3671
      format: []
    note: null
    operation:
    - term: Database search
      uri: http://edamontology.org/operation_2421
    output:
    - data:
        term: JASPAR profile ID
        uri: http://edamontology.org/data_1119
      format:
      - term: JASPAR format
        uri: http://edamontology.org/format_1367
      - term: JSON
        uri: http://edamontology.org/format_3464
      - term: Textual format
        uri: http://edamontology.org/format_2330
      - term: CSV
        uri: http://edamontology.org/format_3752
      - term: TSV
        uri: http://edamontology.org/format_3475
      - term: YAML
        uri: http://edamontology.org/format_3750
  - cmd: null
    input:
    - data:
        term: DNA sequence
        uri: http://edamontology.org/data_3494
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: JASPAR profile ID
        uri: http://edamontology.org/data_1119
      format: []
    note: null
    operation:
    - term: Transcription factor binding site prediction
      uri: http://edamontology.org/operation_0445
    output:
    - data:
        term: JASPAR profile ID
        uri: http://edamontology.org/data_1119
      format: []
  homepage: http://jaspar.genereg.net/
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2023-08-10T10:55:43.068621Z'
  license: CC-BY-4.0
  link:
  - note: null
    type:
    - Discussion forum
    url: https://groups.google.com/g/jaspar
  - note: null
    type:
    - Repository
    url: https://bitbucket.org/CBGR/jaspar/src/master/
  - note: Helpdesk and support for ELIXIR Norway services
    type:
    - Helpdesk
    url: https://elixir.no/helpdesk
  - note: null
    type:
    - Repository
    url: https://doi.org/10.5281/zenodo.6860527
  - note: null
    type:
    - Repository
    url: https://doi.org/10.5281/zenodo.6860555
  - note: null
    type:
    - Software catalogue
    url: https://bioconductor.org/packages/release/data/annotation/html/JASPAR2022.html
  - note: null
    type:
    - Software catalogue
    url: https://pypi.org/project/pyjaspar/
  - note: null
    type:
    - Social media
    url: https://twitter.com/jaspar_db
  maturity: Mature
  name: JASPAR
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID:
  - type: rrid
    value: RRID:SCR_003030
    version: null
  owner: hans
  publication:
  - doi: 10.1093/nar/gkab1113
    metadata:
      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.
      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.
      citationCount: 356
      date: '2022-01-07T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'JASPAR 2022: The 9th release of the open-access database of transcription
        factor binding profiles'
    note: null
    pmcid: PMC8728201
    pmid: '34850907'
    type:
    - Primary
    version: '9'
  - doi: 10.1093/nar/gkz1001
    metadata:
      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.
      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.
      citationCount: 996
      date: '2020-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'JASPAR 2020: Update of the open-Access database of transcription factor
        binding profiles'
    note: null
    pmcid: PMC7145627
    pmid: '31701148'
    type:
    - Primary
    version: '8'
  - doi: 10.1093/nar/gkx1126
    metadata:
      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.
      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.
      citationCount: 879
      date: '2018-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'JASPAR 2018: Update of the open-access database of transcription factor
        binding profiles and its web framework'
    note: null
    pmcid: PMC5753243
    pmid: '29140473'
    type:
    - Primary
    version: '2018'
  - doi: 10.1093/bioinformatics/btx804
    metadata:
      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.
      authors:
      - name: Khan A.
      - name: Mathelier A.
      citationCount: 11
      date: '2018-05-01T00:00:00Z'
      journal: Bioinformatics
      title: 'JASPAR RESTful API: Accessing JASPAR data from any programming language'
    note: null
    pmcid: null
    pmid: '29253085'
    type:
    - Usage
    version: null
  - doi: 10.1093/nar/gkv1176
    metadata:
      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.
      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.
      citationCount: 717
      date: '2016-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'JASPAR 2016: A major expansion and update of the open-access database
        of transcription factor binding profiles'
    note: null
    pmcid: null
    pmid: '26531826'
    type:
    - Primary
    version: '2016'
  - doi: 10.1093/nar/gkt997
    metadata:
      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.
      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.
      citationCount: 789
      date: '2014-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'JASPAR 2014: An extensively expanded and updated open-access database
        of transcription factor binding profiles'
    note: null
    pmcid: null
    pmid: '24194598'
    type:
    - Primary
    version: 5.0_ALPHA
  - doi: 10.1093/nar/gkp950
    metadata:
      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.'
      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.
      citationCount: 478
      date: '2009-11-10T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'JASPAR 2010: The greatly expanded open-access database of transcription
        factor binding profiles'
    note: null
    pmcid: null
    pmid: '19906716'
    type:
    - Primary
    version: '4'
  - doi: 10.1093/nar/gkm955
    metadata:
      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).
      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.
      citationCount: 550
      date: '2008-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'JASPAR, the open access database of transcription factor-binding profiles:
        New content and tools in the 2008 update'
    note: null
    pmcid: null
    pmid: '18006571'
    type:
    - Primary
    version: '3'
  - doi: 10.1093/nar/gkj115
    metadata: null
    note: null
    pmcid: null
    pmid: '16381983'
    type:
    - Primary
    version: '2'
  - doi: 10.1093/nar/gkh012
    metadata: null
    note: null
    pmcid: null
    pmid: '14681366'
    type:
    - Primary
    version: '1'
  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
  toolType:
  - Database portal
  - Web application
  topic:
  - term: Biological databases
    uri: http://edamontology.org/topic_3071
  - term: Transcription factors and regulatory sites
    uri: http://edamontology.org/topic_0749
  - term: Gene regulation
    uri: http://edamontology.org/topic_0204
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  - term: Human biology
    uri: http://edamontology.org/topic_2815
  - term: Plant biology
    uri: http://edamontology.org/topic_0780
  - term: Model organisms
    uri: http://edamontology.org/topic_0621
  validated: 1
  version: []
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