count: 123
list:
- accessibility: Open access
  additionDate: '2021-01-12T12:02:47Z'
  biotoolsCURIE: biotools:mugvre
  biotoolsID: mugvre
  collectionID:
  - RIS3CAT VEIS
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: laia.codo@bsc.es
    fundrefid: null
    gridid: null
    name: Laia Codó
    note: null
    orcidid: https://orcid.org/0000-0002-6797-8746
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Josep Lluís Gelpí
    note: null
    orcidid: http://orcid.org/0000-0002-0566-7723
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: vre@multiscalegenomics.eu
    fundrefid: null
    gridid: null
    name: Multiscale Complex Genomics Community
    note: null
    orcidid: null
    rorid: null
    typeEntity: Consortium
    typeRole:
    - Developer
    url: https://www.multiscalegenomics.eu/
  description: The MuG Virtual Research Environment is an analysis platform for 3D/4D
    genomics analyses. It integrates genomics tools for chromatin dynamics data.
  documentation:
  - note: null
    type:
    - Terms of use
    url: https://www.multiscalegenomics.eu/MuGVRE/terms-of-use/
  - note: null
    type:
    - Quick start guide
    url: http://vre.multiscalegenomics.eu/help/starting.php
  - note: null
    type:
    - Training material
    url: https://www.multiscalegenomics.eu/MuGVRE/training/
  download: []
  editPermission:
    authors:
    - gelpi@ub.edu
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Sequence
        uri: http://edamontology.org/data_2044
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Genome index
        uri: http://edamontology.org/data_3210
      format: []
    note: null
    operation:
    - term: Sequence alignment
      uri: http://edamontology.org/operation_0292
    - term: Read mapping
      uri: http://edamontology.org/operation_3198
    output:
    - data:
        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format:
      - term: BAM
        uri: http://edamontology.org/format_2572
  - cmd: null
    input:
    - data:
        term: Nucleic acid sequence
        uri: http://edamontology.org/data_2977
      format:
      - term: FASTA-like (text)
        uri: http://edamontology.org/format_2200
    - data:
        term: Sequence features
        uri: http://edamontology.org/data_1255
      format:
      - term: GFF
        uri: http://edamontology.org/format_2305
    note: null
    operation:
    - term: Nucleic acid structure prediction
      uri: http://edamontology.org/operation_0475
    - term: Modelling and simulation
      uri: http://edamontology.org/operation_2426
    - term: Nucleic acid folding analysis
      uri: http://edamontology.org/operation_0279
    output:
    - data:
        term: Trajectory data
        uri: http://edamontology.org/data_3870
      format: []
    - data:
        term: Protein structure
        uri: http://edamontology.org/data_1460
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
  - cmd: null
    input:
    - data:
        term: Protein structure
        uri: http://edamontology.org/data_1460
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
    note: null
    operation:
    - term: Molecular docking
      uri: http://edamontology.org/operation_0478
    - term: DNA-binding protein prediction
      uri: http://edamontology.org/operation_3900
    output:
    - data:
        term: Protein complex
        uri: http://edamontology.org/data_2877
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
  - cmd: null
    input:
    - data:
        term: Protein interaction raw data
        uri: http://edamontology.org/data_0905
      format:
      - term: BAM
        uri: http://edamontology.org/format_2572
    note: null
    operation:
    - term: Peak calling
      uri: http://edamontology.org/operation_3222
    - term: Gene regulatory network analysis
      uri: http://edamontology.org/operation_1781
    output:
    - data:
        term: Nucleic acid features
        uri: http://edamontology.org/data_1276
      format:
      - term: BED
        uri: http://edamontology.org/format_3003
  - cmd: null
    input:
    - data:
        term: Protein interaction raw data
        uri: http://edamontology.org/data_0905
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
    note: null
    operation:
    - term: Network analysis
      uri: http://edamontology.org/operation_3927
    - term: Nucleic acid folding analysis
      uri: http://edamontology.org/operation_0279
    output:
    - data:
        term: Topology data
        uri: http://edamontology.org/data_3872
      format:
      - term: pickle
        uri: http://edamontology.org/format_4002
    - data:
        term: Protein interaction data
        uri: http://edamontology.org/data_0906
      format:
      - term: pickle
        uri: http://edamontology.org/format_4002
  - cmd: null
    input:
    - data:
        term: Protein-ligand complex
        uri: http://edamontology.org/data_1461
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
    note: null
    operation:
    - term: Nucleic acid sequence analysis
      uri: http://edamontology.org/operation_2478
    output:
    - data:
        term: Nucleic acid report
        uri: http://edamontology.org/data_2084
      format: []
  - cmd: null
    input:
    - data:
        term: Structure
        uri: http://edamontology.org/data_0883
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
    note: null
    operation:
    - term: Molecular dynamics
      uri: http://edamontology.org/operation_2476
    - term: Nucleic acid structure analysis
      uri: http://edamontology.org/operation_2481
    output:
    - data:
        term: Trajectory data
        uri: http://edamontology.org/data_3870
      format: []
  - cmd: null
    input:
    - data:
        term: Protein interaction raw data
        uri: http://edamontology.org/data_0905
      format:
      - term: BAM
        uri: http://edamontology.org/format_2572
    note: null
    operation:
    - term: Nucleosome position prediction
      uri: http://edamontology.org/operation_0432
    - term: Phasing
      uri: http://edamontology.org/operation_3454
    output:
    - data:
        term: Annotation track
        uri: http://edamontology.org/data_3002
      format:
      - term: GFF
        uri: http://edamontology.org/format_2305
  - cmd: null
    input:
    - data:
        term: Sequence coordinates
        uri: http://edamontology.org/data_2012
      format: []
    - data:
        term: Annotation track
        uri: http://edamontology.org/data_3002
      format: []
    - data:
        term: Simulation
        uri: http://edamontology.org/data_3869
      format: []
    - data:
        term: Structure
        uri: http://edamontology.org/data_0883
      format: []
    note: null
    operation:
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    - term: Structure visualisation
      uri: http://edamontology.org/operation_0570
    - term: Sequence visualisation
      uri: http://edamontology.org/operation_0564
    - term: Network visualisation
      uri: http://edamontology.org/operation_3925
    output: []
  homepage: https://www.multiscalegenomics.eu/
  homepage_status: 0
  language:
  - PHP
  - Python
  lastUpdate: '2025-05-29T11:46:19.236621Z'
  license: Apache-2.0
  link:
  - note: null
    type:
    - Service
    url: http://vre.multiscalegenomics.eu
  - note: null
    type:
    - Repository
    url: https://github.com/Multiscale-Genomics/VRE
  maturity: null
  name: MuGVRE
  operatingSystem: []
  otherID: []
  owner: lcodo
  publication:
  - doi: 10.1101/602474
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: '1.0'
  relation:
  - biotoolsID: nucleosome_dynamics
    type: includes
  - biotoolsID: tadbit
    type: includes
  - biotoolsID: jbrowse
    type: includes
  - biotoolsID: ngl
    type: includes
  toolType:
  - Web application
  - Workbench
  topic:
  - term: DNA packaging
    uri: http://edamontology.org/topic_3176
  - term: ChIP-seq
    uri: http://edamontology.org/topic_3169
  - term: Nucleic acid structure analysis
    uri: http://edamontology.org/topic_0097
  - term: Molecular modelling
    uri: http://edamontology.org/topic_2275
  validated: 1
  version:
  - '1.0'
- accessibility: Open access
  additionDate: '2019-02-13T17:01:40Z'
  biotoolsCURIE: biotools:Jalview
  biotoolsID: Jalview
  collectionID:
  - ELIXIR-UK
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Jim Procter
    note: null
    orcidid: https://orcid.org/0000-0002-7865-7382
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://www.lifesci.dundee.ac.uk/people/jim-procter
  - email: null
    fundrefid: null
    gridid: null
    name: Geoff Barton
    note: null
    orcidid: https://orcid.org/0000-0002-9014-5355
    rorid: null
    typeEntity: null
    typeRole: []
    url: https://www.lifesci.dundee.ac.uk/people/geoff-barton
  description: Jalview is a free program for multiple sequence alignment editing,
    visualisation and analysis. Use it to view and edit sequence alignments, analyse
    them with phylogenetic trees and principal components analysis (PCA) plots and
    explore molecular structures and annotation.
  documentation:
  - note: null
    type:
    - Citation instructions
    url: https://www.jalview.org/about/citation
  - note: Hands-on exercises, Training courses and Training videos
    type:
    - Training material
    url: https://www.jalview.org/training/
  - note: null
    type:
    - FAQ
    url: https://www.jalview.org/help/faq
  - note: null
    type:
    - User manual
    url: https://www.jalview.org/help/documentation/
  download:
  - note: null
    type: Downloads page
    url: https://www.jalview.org/download
    version: null
  - note: null
    type: Source code
    url: https://www.jalview.org/download/source/
    version: null
  - note: Binaries for all platforms
    type: Binaries
    url: https://www.jalview.org/download/?os=all
    version: null
  - note: null
    type: Icon
    url: https://www.jalview.org/favicon.svg
    version: null
  - note: Executable JAR file
    type: Binaries
    url: https://www.jalview.org/download/other/jar/
    version: null
  editPermission:
    authors:
    - ben_s
    - jimprocter
    type: group
  elixirCommunity: []
  elixirNode:
  - UK
  elixirPlatform:
  - Tools
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format:
      - term: GFF3-seq
        uri: http://edamontology.org/format_1939
      - term: ClustalW format
        uri: http://edamontology.org/format_1982
      - term: Stockholm format
        uri: http://edamontology.org/format_1961
      - term: FASTA-aln
        uri: http://edamontology.org/format_1984
      - term: GFF2-seq
        uri: http://edamontology.org/format_1938
      - term: FASTA
        uri: http://edamontology.org/format_1929
      - term: nbrf/pir
        uri: http://edamontology.org/format_1948
      - term: BioJSON (Jalview)
        uri: http://edamontology.org/format_3774
      - term: PHYLIP format
        uri: http://edamontology.org/format_1997
      - term: BLC
        uri: http://edamontology.org/format_3313
      - term: RNAML
        uri: http://edamontology.org/format_3311
      - term: GCG MSF
        uri: http://edamontology.org/format_1947
      - term: Pileup
        uri: http://edamontology.org/format_3015
      - term: mmCIF
        uri: http://edamontology.org/format_1477
      - term: VCF
        uri: http://edamontology.org/format_3016
      - term: Format
        uri: http://edamontology.org/format_1915
    - data:
        term: Structure alignment
        uri: http://edamontology.org/data_0886
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
    note: 'Other Input formats:

      AMSA (.amsa);

      JnetFile (.concise, .jnet);

      PFAM (.pfam);

      Substitution matrix (.matrix);

      Jalview Project File (.jvp);

      Jalview Feature File (.features, .jvfeatures);

      Jalview Annotations File (.annotations, .jvannotations);

      Predicted Aligned Error (PAE) Matrix File (.json)

      ...

      Other Output formats:

      PFAM (.pfam);

      BioJS (.biojs) (interactive HTML/Javascript);

      Jalview Project File (.jvp);'
    operation:
    - term: Sequence visualisation
      uri: http://edamontology.org/operation_0564
    - term: Phylogenetic tree analysis
      uri: http://edamontology.org/operation_0324
    - term: Sequence alignment editing
      uri: http://edamontology.org/operation_3081
    output:
    - data:
        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format:
      - term: nbrf/pir
        uri: http://edamontology.org/format_1948
      - term: JSON
        uri: http://edamontology.org/format_3464
      - term: Stockholm format
        uri: http://edamontology.org/format_1961
      - term: FASTA
        uri: http://edamontology.org/format_1929
      - term: PHYLIP format
        uri: http://edamontology.org/format_1997
      - term: BLC
        uri: http://edamontology.org/format_3313
      - term: BioJSON (Jalview)
        uri: http://edamontology.org/format_3774
      - term: GCG MSF
        uri: http://edamontology.org/format_1947
      - term: Pileup
        uri: http://edamontology.org/format_3015
      - term: ClustalW format
        uri: http://edamontology.org/format_1982
    - data:
        term: Plot
        uri: http://edamontology.org/data_2884
      format:
      - term: PNG
        uri: http://edamontology.org/format_3603
      - term: HTML
        uri: http://edamontology.org/format_2331
      - term: EPS
        uri: http://edamontology.org/format_3466
      - term: SVG
        uri: http://edamontology.org/format_3604
      - term: Format
        uri: http://edamontology.org/format_1915
  homepage: https://www.jalview.org/
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-28T10:07:42.658684Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Discussion forum
    url: https://discourse.jalview.org/
  - note: null
    type:
    - Issue tracker
    url: https://issues.jalview.org/
  - note: Latest development version
    type:
    - Other
    url: https://www.jalview.org/development/jalview_develop/
  - note: null
    type:
    - Repository
    url: https://source.jalview.org/crucible/browse/jalview
  - note: Twitter feed
    type:
    - Social media
    url: https://twitter.com/Jalview
  - note: YouTube training videos
    type:
    - Social media
    url: https://www.youtube.com/channel/UCIjpnvZB770yz7ftbrJ0tfw
  maturity: Mature
  name: Jalview
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: ben_s
  publication:
  - doi: 10.1093/bioinformatics/btp033
    metadata: null
    note: null
    pmcid: PMC2672624
    pmid: '19151095'
    type: []
    version: null
  relation:
  - biotoolsID: jabaws
    type: uses
  - biotoolsID: chimera
    type: uses
  - biotoolsID: chimerax
    type: uses
  - biotoolsID: pymol
    type: uses
  - biotoolsID: bioconda
    type: includedIn
  - biotoolsID: 3d-beacons
    type: uses
  - biotoolsID: uniprot
    type: uses
  - biotoolsID: pfam
    type: uses
  - biotoolsID: ensembl
    type: uses
  - biotoolsID: pdb
    type: uses
  - biotoolsID: rfam
    type: uses
  toolType:
  - Desktop application
  - Command-line tool
  topic:
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  - term: Data visualisation
    uri: http://edamontology.org/topic_0092
  validated: 1
  version:
  - 2.11.4.1
- accessibility: null
  additionDate: '2016-06-02T02:47:10Z'
  biotoolsCURIE: biotools:msa
  biotoolsID: msa
  collectionID:
  - Rostlab tools
  - Bioconductor
  - BioJS
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Sebastian Wilzbach
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Ian Sillitoe
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Guy Yachdav
    note: null
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    rorid: null
    typeEntity: null
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Benedikt Rauscher
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Tatyana Goldberg
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Technische Universität München
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Google Summer of Code (GSoC) 2014
    note: null
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    rorid: null
    typeEntity: Funding agency
    typeRole:
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    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: BioJS
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://github.com/wilzbach/msa
  - email: bodenhofer@bioinf.jku.at
    fundrefid: null
    gridid: null
    name: Ulrich Bodenhofer
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Display multiple-sequence alignment. The tool is also available as
    R/BioConductor interface to the multiple sequence alignment algorithms ClustalW,
    ClustalOmega, and Muscle. All three algorithms are integrated in the package,
    therefore, they do not depend on any external software tools and are available
    for all major platforms.
  documentation:
  - note: null
    type:
    - Terms of use
    url: https://github.com/wilzbach/msa/blob/master/LICENSE
  - note: null
    type:
    - General
    url: http://msa.biojs.net
  download:
  - note: null
    type: Source code
    url: https://github.com/wilzbach/msa
    version: null
  - note: null
    type: Binaries
    url: https://cdn.bio.sh/
    version: null
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format:
      - term: ClustalW format
        uri: http://edamontology.org/format_1982
      - term: FASTA-aln
        uri: http://edamontology.org/format_1984
    note: 'Visualizes multiple sequence alignment, calculates conservation, shows
      sequence logo, applies multiple color schemes A multiple sequence alignment
      (ClustalW, FASTA, ...) Exports selected sequences and regions from the alignment
      Images are exported in PNG Export sequences in FASTA format Export features
      in GFF

      NOTE: Actually, all these output types of data should instead be under separate
      "constant" operations, while the visualisation should be an unary operation,
      perhaps without an output.'
    operation:
    - term: Sequence visualisation
      uri: http://edamontology.org/operation_0564
    output:
    - data:
        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format:
      - term: FASTA-aln
        uri: http://edamontology.org/format_1984
    - data:
        term: Sequence alignment image
        uri: http://edamontology.org/data_1711
      format:
      - term: Image format
        uri: http://edamontology.org/format_3547
    - data:
        term: Sequence set
        uri: http://edamontology.org/data_0850
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Feature table
        uri: http://edamontology.org/data_1270
      format:
      - term: GFF
        uri: http://edamontology.org/format_2305
  - cmd: null
    input:
    - data:
        term: Nucleic acid sequence
        uri: http://edamontology.org/data_2977
      format:
      - term: nbrf/pir
        uri: http://edamontology.org/format_1948
      - term: FASTA
        uri: http://edamontology.org/format_1929
      - term: GCG
        uri: http://edamontology.org/format_1935
      - term: PHYLIP format
        uri: http://edamontology.org/format_1997
      - term: EMBL format
        uri: http://edamontology.org/format_1927
      - term: GenBank format
        uri: http://edamontology.org/format_1936
    - data:
        term: Protein sequence
        uri: http://edamontology.org/data_2976
      format:
      - term: nbrf/pir
        uri: http://edamontology.org/format_1948
      - term: FASTA
        uri: http://edamontology.org/format_1929
      - term: GCG
        uri: http://edamontology.org/format_1935
      - term: PHYLIP format
        uri: http://edamontology.org/format_1997
      - term: EMBL format
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        molecular biology. The project aims to enable interdisciplinary research,
        collaboration and rapid development of scientific software. Based on the statistical
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      authors:
      - name: Huber W.
      - name: Carey V.J.
      - name: Gentleman R.
      - name: Anders S.
      - name: Carlson M.
      - name: Carvalho B.S.
      - name: Bravo H.C.
      - name: Davis S.
      - name: Gatto L.
      - name: Girke T.
      - name: Gottardo R.
      - name: Hahne F.
      - name: Hansen K.D.
      - name: Irizarry R.A.
      - name: Lawrence M.
      - name: Love M.I.
      - name: MaCdonald J.
      - name: Obenchain V.
      - name: Oles A.K.
      - name: Pages H.
      - name: Reyes A.
      - name: Shannon P.
      - name: Smyth G.K.
      - name: Tenenbaum D.
      - name: Waldron L.
      - name: Morgan M.
      citationCount: 2315
      date: '2015-01-01T00:00:00Z'
      journal: Nature Methods
      title: Orchestrating high-throughput genomic analysis with Bioconductor
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    pmcid: PMC4509590
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  description: A database designed to help the mycologist community to access to fungal
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        species barcodes or conserved sequences containing a high-quality phylogenetic
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        the adoption of the phylogenetic species concept. Such analysis requires that
        the reference sequences are well identified and deposited in public-access
        databases. However, many entries in the public sequence databases are problematic
        in terms of quality and reliability and these data require screening to ensure
        correct phylogenetic interpretation. Methods and Principal Findings: To facilitate
        phylogenetic inferences and phylogenetic assignment, we introduce a fungal
        sequence database. The database PHYMYCO-DB comprises fungal sequences from
        GenBank that have been filtered to satisfy stringent sequence quality criteria.
        For the first release, two widely used molecular taxonomic markers were chosen:
        the nuclear SSU rRNA and EF1-α gene sequences. Following the automatic extraction
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        while preserving relevant sequences useful for phylogenetic studies. As a
        result of curation, ~20% of the automatically filtered sequences have been
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        The PHYMYCO-DB is accessible through the URL http://phymycodb.genouest.org.
        © 2012 Mahé et al.'
      authors:
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      - name: Duhamel M.
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      - name: Guillot L.
      - name: Sarbu L.
      - name: Bretaudeau A.
      - name: Collin O.
      - name: Dufresne A.
      - name: Kiers E.T.
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      citationCount: 37
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      journal: PLoS ONE
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  description: Searches Ensembl Fungi sequences using Exonerate.
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        access of genomic annotation from chordates and key model organisms. It provides
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        two data updates for the previous human assembly, GRCh37, through a dedicated
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        data. REST is now capable of larger-scale analysis and our regulatory data
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        genes, variants and phenotypes. Our data is made available without restriction
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      authors:
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      - name: Akanni W.
      - name: Amode M.R.
      - name: Barrell D.
      - name: Billis K.
      - name: Carvalho-Silva D.
      - name: Cummins C.
      - name: Clapham P.
      - name: Fitzgerald S.
      - name: Gil L.
      - name: Giron C.G.
      - name: Gordon L.
      - name: Hourlier T.
      - name: Hunt S.E.
      - name: Janacek S.H.
      - name: Johnson N.
      - name: Juettemann T.
      - name: Keenan S.
      - name: Lavidas I.
      - name: Martin F.J.
      - name: Maurel T.
      - name: McLaren W.
      - name: Murphy D.N.
      - name: Nag R.
      - name: Nuhn M.
      - name: Parker A.
      - name: Patricio M.
      - name: Pignatelli M.
      - name: Rahtz M.
      - name: Riat H.S.
      - name: Sheppard D.
      - name: Taylor K.
      - name: Thormann A.
      - name: Vullo A.
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  description: JABAWS stands for JAva Bioinformatics Analysis Web Services. It is
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    metadata:
      abstract: 'Summary: JABAWS is a web services framework that simplifies the deployment
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        application through simple configuration files. The JABAWS command-line client
        allows integration of JABAWS services into conventional scripts. © The Author(s)
        2011. Published by Oxford University Press.'
      authors:
      - name: Troshin P.V.
      - name: Procter J.B.
      - name: Barton G.J.
      citationCount: 96
      date: '2011-07-01T00:00:00Z'
      journal: Bioinformatics
      title: Java bioinformatics analysis web services for multiple sequence alignment-JABAWS:MSA
    note: null
    pmcid: PMC3129525
    pmid: '21593132'
    type:
    - Primary
    version: null
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    typeEntity: Person
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    url: http://www.compbio.dundee.ac.uk/jabaws/contacts.html
  description: Finds the best global alignment for a set of input sequences (nucleic
    acid or protein).
  documentation:
  - note: null
    type:
    - User manual
    url: http://www.compbio.dundee.ac.uk/jabaws/man_about.html
  - note: null
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    - data:
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  - Java
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    metadata:
      abstract: 'Summary: JABAWS is a web services framework that simplifies the deployment
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        provides clients full access to each application''s parameters, allows administrators
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        application through simple configuration files. The JABAWS command-line client
        allows integration of JABAWS services into conventional scripts. © The Author(s)
        2011. Published by Oxford University Press.'
      authors:
      - name: Troshin P.V.
      - name: Procter J.B.
      - name: Barton G.J.
      citationCount: 96
      date: '2011-07-01T00:00:00Z'
      journal: Bioinformatics
      title: Java bioinformatics analysis web services for multiple sequence alignment-JABAWS:MSA
    note: null
    pmcid: PMC3129525
    pmid: '21593132'
    type:
    - Review
    version: null
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  validated: 1
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  additionDate: '2015-08-03T09:36:09Z'
  biotoolsCURIE: biotools:tcoffee
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    name: Cedric Notredame
    note: null
    orcidid: null
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    typeEntity: Person
    typeRole:
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    url: null
  description: A multiple sequence alignment package that can be used for DNA, RNA
    and protein sequences. It can be used to align sequences or to combine the output
    of other alignment methods (Clustal, Mafft, Probcons, Muscle...) into one unique
    alignment.
  documentation:
  - note: null
    type:
    - General
    url: http://www.tcoffee.org/Projects/tcoffee/
  - note: null
    type:
    - Installation instructions
    url: http://www.tcoffee.org/Projects/tcoffee/#INSTALLATION
  - note: T-Coffee README file
    type:
    - General
    url: http://www.tcoffee.org/Projects/tcoffee/documentation/README
  - note: null
    type:
    - FAQ
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  license: GPL-3.0
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  maturity: Mature
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  publication:
  - doi: 10.1006/jmbi.2000.4042
    metadata:
      abstract: We describe a new method (T-Coffee) for multiple sequence alignment
        that provides a dramatic improvement in accuracy with a modest sacrifice in
        speed as compared to the most commonly used alternatives. The method is broadly
        based on the popular progressive approach to multiple alignment but avoids
        the most serious pitfalls caused by the greedy nature of this algorithm. With
        T-Coffee we pre-process a data set of all pair-wise alignments between the
        sequences. This provides us with a library of alignment information that can
        be used to guide the progressive alignment. Intermediate alignments are then
        based not only on the sequences to be aligned next but also on how all of
        the sequences align with each other. This alignment information can be derived
        from heterogeneous sources such as a mixture of alignment programs and/or
        structure superposition. Here, we illustrate the power of the approach by
        using a combination of local and global pair-wise alignments to generate the
        library. The resulting alignments are significantly more reliable, as determined
        by comparison with a set of 141 test cases, than any of the popular alternatives
        that we tried. The improvement, especially clear with the more difficult test
        cases, is always visible, regardless of the phylogenetic spread of the sequences
        in the tests. (C) 2000 Academic Press.
      authors:
      - name: Notredame C.
      - name: Higgins D.G.
      - name: Heringa J.
      citationCount: 5803
      date: '2000-09-08T00:00:00Z'
      journal: Journal of Molecular Biology
      title: 'T-coffee: A novel method for fast and accurate multiple sequence alignment'
    note: null
    pmcid: null
    pmid: '10964570'
    type:
    - Primary
    version: null
  relation: []
  toolType:
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    uri: http://edamontology.org/topic_0080
  validated: 1
  version:
  - '1'
- accessibility: null
  additionDate: '2015-08-03T09:36:10Z'
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    typeEntity: Person
    typeRole:
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    url: http://www.compbio.dundee.ac.uk/jabaws/contacts.html
  description: Multiple sequence algnment tool.
  documentation:
  - note: null
    type:
    - User manual
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  - note: null
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  publication:
  - doi: 10.1093/bioinformatics/btr304
    metadata:
      abstract: 'Summary: JABAWS is a web services framework that simplifies the deployment
        of web services for bioinformatics. JABAWS:MSA provides services for five
        multiple sequence alignment (MSA) methods (Probcons, T-coffee, Muscle, Mafft
        and ClustalW), and is the system employed by the Jalview multiple sequence
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        is provided as a Virtual Appliance (VA), which can be run on most operating
        systems that support a virtualization environment such as VMware or Oracle
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        provides clients full access to each application''s parameters, allows administrators
        to specify named parameter preset combinations and execution limits for each
        application through simple configuration files. The JABAWS command-line client
        allows integration of JABAWS services into conventional scripts. © The Author(s)
        2011. Published by Oxford University Press.'
      authors:
      - name: Troshin P.V.
      - name: Procter J.B.
      - name: Barton G.J.
      citationCount: 96
      date: '2011-07-01T00:00:00Z'
      journal: Bioinformatics
      title: Java bioinformatics analysis web services for multiple sequence alignment-JABAWS:MSA
    note: null
    pmcid: PMC3129525
    pmid: '21593132'
    type:
    - Review
    version: null
  relation: []
  toolType:
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  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  validated: 1
  version:
  - '1'
- accessibility: null
  additionDate: '2017-01-13T13:13:56Z'
  biotoolsCURIE: biotools:bwa
  biotoolsID: bwa
  collectionID:
  - BWA
  confidence_flag: null
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  - email: me@liheng.org
    fundrefid: null
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    name: Heng Li
    note: null
    orcidid: http://orcid.org/0000-0003-4874-2874
    rorid: null
    typeEntity: Person
    typeRole:
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  description: Fast, accurate, memory-efficient aligner for short and long sequencing
    reads
  documentation:
  - note: null
    type:
    - User manual
    url: http://bio-bwa.sourceforge.net/bwa.shtml
  download:
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    version: null
  - note: null
    type: Container file
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    version: null
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    input:
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    note: Index database sequences in the FASTA format. database
    operation:
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  - cmd: null
    input:
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      - term: FASTQ
        uri: http://edamontology.org/format_1930
    note: Align 70bp-1Mbp query sequences with the BWA-MEM algorithm. Briefly, the
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      then extending seeds with the affine-gap Smith-Waterman algorithm (SW). The
      BWA-MEM algorithm performs local alignment. It may produce multiple primary
      alignments for different part of a query sequence. This is a crucial feature
      for long sequences. However, some tools such as Picards markDuplicates does
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      split hits as secondary.
    operation:
    - term: Sequence alignment
      uri: http://edamontology.org/operation_0292
    output:
    - data:
        term: Alignment
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      format: []
  - cmd: null
    input:
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    - data:
        term: Sequence
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      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
    note: Find the SA coordinates of the input reads. reference sequence query sequence
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    - term: Read mapping
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    - term: Sequence alignment
      uri: http://edamontology.org/operation_0292
    output:
    - data:
        term: Sequence coordinates
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      format: []
  - cmd: null
    input:
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    - data:
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        uri: http://edamontology.org/format_1930
    - data:
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      format: []
    note: Generate alignments in the SAM format given single-end reads. Repetitive
      hits will be randomly chosen reference sequence query sequence
    operation:
    - term: Generation
      uri: http://edamontology.org/operation_3429
    - term: Sequence alignment
      uri: http://edamontology.org/operation_0292
    output:
    - data:
        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format:
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  - cmd: null
    input:
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    - data:
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      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
    note: Generate alignments in the SAM format given paired-end reads. Repetitive
      read pairs will be placed randomly. reference sequence
    operation:
    - term: Generation
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    - term: Sequence alignment
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    output:
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    - data:
        term: Sequence
        uri: http://edamontology.org/data_2044
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
    note: Align query sequences in the in.fq file reference sequence
    operation:
    - term: Sequence alignment
      uri: http://edamontology.org/operation_0292
    output:
    - data:
        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format: []
  homepage: http://bio-bwa.sourceforge.net
  homepage_status: 0
  language:
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  lastUpdate: '2024-11-25T14:09:49.679089Z'
  license: MIT
  link: []
  maturity: Mature
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  - Mac
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  owner: seqwiki_import
  publication:
  - doi: 10.1093/bioinformatics/btp324
    metadata:
      abstract: 'Motivation: The enormous amount of short reads generated by the new
        DNA sequencing technologies call for the development of fast and accurate
        read alignment programs. A first generation of hash table-based methods has
        been developed, including MAQ, which is accurate, feature rich and fast enough
        to align short reads from a single individual. However, MAQ does not support
        gapped alignment for single-end reads, which makes it unsuitable for alignment
        of longer reads where indels may occur frequently. The speed of MAQ is also
        a concern when the alignment is scaled up to the resequencing of hundreds
        of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA),
        a new read alignment package that is based on backward search with Burrows-Wheeler
        Transform (BWT), to efficiently align short sequencing reads against a large
        reference sequence such as the human genome, allowing mismatches and gaps.
        BWA supports both base space reads, e.g. from Illumina sequencing machines,
        and color space reads from AB SOLiD machines. Evaluations on both simulated
        and real data suggest that BWA is ∼10-20× faster than MAQ, while achieving
        similar accuracy. In addition, BWA outputs alignment in the new standard SAM
        (Sequence Alignment/Map) format. Variant calling and other downstream analyses
        after the alignment can be achieved with the open source SAMtools software
        package. © 2009 The Author(s).'
      authors:
      - name: Li H.
      - name: Durbin R.
      citationCount: 33667
      date: '2009-07-01T00:00:00Z'
      journal: Bioinformatics
      title: Fast and accurate short read alignment with Burrows-Wheeler transform
    note: null
    pmcid: PMC2705234
    pmid: '19451168'
    type:
    - Primary
    version: null
  - doi: 10.1186/1471-2105-14-184
    metadata:
      abstract: 'Background: The development of next-generation sequencing instruments
        has led to the generation of millions of short sequences in a single run.
        The process of aligning these reads to a reference genome is time consuming
        and demands the development of fast and accurate alignment tools. However,
        the current proposed tools make different compromises between the accuracy
        and the speed of mapping. Moreover, many important aspects are overlooked
        while comparing the performance of a newly developed tool to the state of
        the art. Therefore, there is a need for an objective evaluation method that
        covers all the aspects. In this work, we introduce a benchmarking suite to
        extensively analyze sequencing tools with respect to various aspects and provide
        an objective comparison.Results: We applied our benchmarking tests on 9 well
        known mapping tools, namely, Bowtie, Bowtie2, BWA, SOAP2, MAQ, RMAP, GSNAP,
        Novoalign, and mrsFAST (mrFAST) using synthetic data and real RNA-Seq data.
        MAQ and RMAP are based on building hash tables for the reads, whereas the
        remaining tools are based on indexing the reference genome. The benchmarking
        tests reveal the strengths and weaknesses of each tool. The results show that
        no single tool outperforms all others in all metrics. However, Bowtie maintained
        the best throughput for most of the tests while BWA performed better for longer
        read lengths. The benchmarking tests are not restricted to the mentioned tools
        and can be further applied to others.Conclusion: The mapping process is still
        a hard problem that is affected by many factors. In this work, we provided
        a benchmarking suite that reveals and evaluates the different factors affecting
        the mapping process. Still, there is no tool that outperforms all of the others
        in all the tests. Therefore, the end user should clearly specify his needs
        in order to choose the tool that provides the best results. © 2013 Hatem et
        al.; licensee BioMed Central Ltd.'
      authors:
      - name: Hatem A.
      - name: Bozdag D.
      - name: Toland A.E.
      - name: Catalyurek U.V.
      citationCount: 146
      date: '2013-06-07T00:00:00Z'
      journal: BMC Bioinformatics
      title: Benchmarking short sequence mapping tools
    note: null
    pmcid: PMC3694458
    pmid: '23758764'
    type:
    - Benchmarking study
    version: null
  - doi: 10.1016/j.ygeno.2017.03.001
    metadata:
      abstract: Massive data produced due to the advent of next-generation sequencing
        (NGS) technology is widely used for biological researches and medical diagnosis.
        The crucial step in NGS analysis is read alignment or mapping which is computationally
        intensive and complex. The mapping bias tends to affect the downstream analysis,
        including detection of polymorphisms. In order to provide guidelines to the
        biologist for suitable selection of aligners; we have evaluated and benchmarked
        5 different aligners (BWA, Bowtie2, NovoAlign, Smalt and Stampy) and their
        mapping bias based on characteristics of 5 microbial genomes. Two million
        simulated read pairs of various sizes (36 bp, 50 bp, 72 bp, 100 bp, 125 bp,
        150 bp, 200 bp, 250 bp and 300 bp) were aligned. Specific alignment features
        such as sensitivity of mapping, percentage of properly paired reads, alignment
        time and effect of tandem repeats on incorrectly mapped reads were evaluated.
        BWA showed faster alignment followed by Bowtie2 and Smalt. NovoAlign and Stampy
        were comparatively slower. Most of the aligners showed high sensitivity towards
        long reads (> 100 bp) mapping. On the other hand NovoAlign showed higher sensitivity
        towards both short reads (36 bp, 50 bp, 72 bp) and long reads (> 100 bp) mappings;
        It also showed higher sensitivity towards mapping a complex genome like Plasmodium
        falciparum. The percentage of properly paired reads aligned by NovoAlign,
        BWA and Stampy were markedly higher. None of the aligners outperforms the
        others in the benchmark, however the aligners perform differently with genome
        characteristics. We expect that the results from this study will be useful
        for the end user to choose aligner, thus enhance the accuracy of read mapping.
      authors:
      - name: Thankaswamy-Kosalai S.
      - name: Sen P.
      - name: Nookaew I.
      citationCount: 54
      date: '2017-07-01T00:00:00Z'
      journal: Genomics
      title: Evaluation and assessment of read-mapping by multiple next-generation
        sequencing aligners based on genome-wide characteristics
    note: null
    pmcid: null
    pmid: '28286147'
    type: []
    version: null
  - doi: 10.1186/1471-2164-15-264
    metadata:
      abstract: 'Background: The rapid evolution in high-throughput sequencing (HTS)
        technologies has opened up new perspectives in several research fields and
        led to the production of large volumes of sequence data. A fundamental step
        in HTS data analysis is the mapping of reads onto reference sequences. Choosing
        a suitable mapper for a given technology and a given application is a subtle
        task because of the difficulty of evaluating mapping algorithms.Results: In
        this paper, we present a benchmark procedure to compare mapping algorithms
        used in HTS using both real and simulated datasets and considering four evaluation
        criteria: computational resource and time requirements, robustness of mapping,
        ability to report positions for reads in repetitive regions, and ability to
        retrieve true genetic variation positions. To measure robustness, we introduced
        a new definition for a correctly mapped read taking into account not only
        the expected start position of the read but also the end position and the
        number of indels and substitutions. We developed CuReSim, a new read simulator,
        that is able to generate customized benchmark data for any kind of HTS technology
        by adjusting parameters to the error types. CuReSim and CuReSimEval, a tool
        to evaluate the mapping quality of the CuReSim simulated reads, are freely
        available. We applied our benchmark procedure to evaluate 14 mappers in the
        context of whole genome sequencing of small genomes with Ion Torrent data
        for which such a comparison has not yet been established.Conclusions: A benchmark
        procedure to compare HTS data mappers is introduced with a new definition
        for the mapping correctness as well as tools to generate simulated reads and
        evaluate mapping quality. The application of this procedure to Ion Torrent
        data from the whole genome sequencing of small genomes has allowed us to validate
        our benchmark procedure and demonstrate that it is helpful for selecting a
        mapper based on the intended application, questions to be addressed, and the
        technology used. This benchmark procedure can be used to evaluate existing
        or in-development mappers as well as to optimize parameters of a chosen mapper
        for any application and any sequencing platform. © 2014 Caboche et al.; licensee
        BioMed Central Ltd.'
      authors:
      - name: Caboche S.
      - name: Audebert C.
      - name: Lemoine Y.
      - name: Hot D.
      citationCount: 66
      date: '2014-04-05T00:00:00Z'
      journal: BMC Genomics
      title: 'Comparison of mapping algorithms used in high-throughput sequencing:
        Application to Ion Torrent data'
    note: null
    pmcid: PMC4051166
    pmid: '24708189'
    type:
    - Benchmarking study
    version: null
  - doi: 10.1093/bioinformatics/btu146
    metadata:
      abstract: 'Motivation: Next-generation sequencing has become an important tool
        in molecular biology. Various protocols to investigate genomic, transcriptomic
        and epigenomic features across virtually all species and tissues have been
        devised. For most of these experiments, one of the first crucial steps of
        bioinformatic analysis is the mapping of reads to reference genomes. Results:
        Here, we present thorough benchmarks of our read aligner segemehl in comparison
        with other state-of-the-art methods. Furthermore, we introduce the tool lack
        to rescue unmapped RNA-seq reads which works in conjunction with segemehl
        and many other frequently used split-read aligners. © The Author 2014.'
      authors:
      - name: Otto C.
      - name: Stadler P.F.
      - name: Hoffmann S.
      citationCount: 71
      date: '2014-07-01T00:00:00Z'
      journal: Bioinformatics
      title: Lacking alignments? The next-generation sequencing mapper segemehl revisited
    note: null
    pmcid: null
    pmid: '24626854'
    type: []
    version: null
  - doi: 10.1093/bioinformatics/btp698
    metadata:
      abstract: 'Motivation: Many programs for aligning short sequencing reads to
        a reference genome have been developed in the last 2 years. Most of them are
        very efficient for short reads but inefficient or not applicable for reads
        >200 bp because the algorithms are heavily and specifically tuned for short
        queries with low sequencing error rate. However, some sequencing platforms
        already produce longer reads and others are expected to become available soon.
        For longer reads, hashingbased software such as BLAT and SSAHA2 remain the
        only choices. Nonetheless, these methods are substantially slower than short-read
        aligners in terms of aligned bases per unit time. Results: We designed and
        implemented a new algorithm, Burrows-Wheeler Aligner''s Smith-Waterman Alignment
        (BWA-SW), to align long sequences up to 1Mb against a large sequence database
        (e.g. the human genome) with a few gigabytes of memory. The algorithm is as
        accurate as SSAHA2, more accurate than BLAT, and is several to tens of times
        faster than both. Availability: http://bio-bwa.sourceforge.net. Contact: rd@sanger.ac.uk
        © The Author(s) 2010. Published by Oxford University Press.'
      authors:
      - name: Li H.
      - name: Durbin R.
      citationCount: 8584
      date: '2010-01-15T00:00:00Z'
      journal: Bioinformatics
      title: Fast and accurate long-read alignment with Burrows-Wheeler transform
    note: null
    pmcid: PMC2828108
    pmid: '20080505'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  - Workbench
  topic:
  - term: Mapping
    uri: http://edamontology.org/topic_0102
  validated: 1
  version: []
- accessibility: null
  additionDate: '2016-04-22T09:22:48Z'
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    gridid: null
    name: Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben
    note: null
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    rorid: null
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    url: null
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    note: null
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    typeEntity: Institute
    typeRole:
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    url: null
  - email: scholz@ipk-gatersleben.de
    fundrefid: null
    gridid: null
    name: Dr. Uwe Scholz
    note: null
    orcidid: null
    rorid: null
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    typeRole:
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    url: null
  - email: scholz@ipk-gatersleben.de
    fundrefid: null
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    name: Dr. Uwe Scholz
    note: null
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    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  description: A homology search against the current barley sequences resources is
    provided. The complete sequences data set comprises the whole genome shotgun assemblies
    of the cultivars Morex, Barke and Bowman as well as the high and low confidence
    gene sets. The newest POPSEQ anchoring data is integrated. Furthermore, the barley
    exome capture targets are provided. Additionally, resources like bacterial artificial
    chromosome assemblies, BAC end sequences and full length cDNAs are included.
  documentation:
  - note: null
    type:
    - Citation instructions
    url: http://dx.doi.org/10.3835/plantgenome2015.06.0038
  - note: null
    type:
    - General
    url: http://webblast.ipk-gatersleben.de/barley_ibsc/docs/blast_databases.html
  - note: null
    type:
    - General
    url: http://webblast.ipk-gatersleben.de/ryeselect/docs/blast_databases.html
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    input:
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    note: null
    operation:
    - term: Sequence similarity search
      uri: http://edamontology.org/operation_0346
    output:
    - data:
        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format:
      - term: Alignment format
        uri: http://edamontology.org/format_1921
  homepage: http://webblast.ipk-gatersleben.de
  homepage_status: 0
  language:
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  lastUpdate: '2024-11-25T14:07:20.696381Z'
  license: null
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  maturity: null
  name: IPK BLAST Server
  operatingSystem:
  - Linux
  otherID: []
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  publication:
  - doi: 10.3835/plantgenome2015.06.0038
    metadata:
      abstract: The genome sequences of many important Triticeae species, including
        bread wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.), remained
        uncharacterized for a long time because their high repeat content, large sizes,
        and polyploidy. As a result of improvements in sequencing technologies and
        novel analyses strategies, several of these have recently been deciphered.
        These efforts have generated new insights into Triticeae biology and genome
        organization and have important implications for downstream usage by breeders,
        experimental biologists, and comparative genomicists. transPLANT (http://www.transplantdb.eu)
        is an EU-funded project aimed at constructing hardware, software, and data
        infrastructure for genome-scale research in the life sciences. Since the Triticeae
        data are intrinsically complex, heterogenous, and distributed, the transPLANT
        consortium has undertaken efforts to develop common data formats and tools
        that enable the exchange and integration of data from distributed resources.
        Here we present an overview of the individual Triticeae genome resources hosted
        by transPLANT partners, introduce the objectives of transPLANT, and outline
        common developments and interfaces supporting integrated data access.
      authors:
      - name: Spannagl M.
      - name: Alaux M.
      - name: Lange M.
      - name: Bolser D.M.
      - name: Bader K.C.
      - name: Letellier T.
      - name: Kimmel E.
      - name: Flores R.
      - name: Pommier C.
      - name: Kerhornou A.
      - name: Walts B.
      - name: Nussbaumer T.
      - name: Grabmuller C.
      - name: Chen J.
      - name: Colmsee C.
      - name: Beier S.
      - name: Mascher M.
      - name: Schmutzer T.
      - name: Arend D.
      - name: Thanki A.
      - name: Ramirez-Gonzalez R.
      - name: Ayling M.
      - name: Ayling S.
      - name: Caccamo M.
      - name: Mayer K.F.X.
      - name: Scholz U.
      - name: Steinbach D.
      - name: Quesneville H.
      - name: Kersey P.J.
      citationCount: 6
      date: '2016-03-01T00:00:00Z'
      journal: Plant Genome
      title: TransPLANT resources for triticeae genomic data
    note: null
    pmcid: null
    pmid: '27898761'
    type:
    - Primary
    version: null
  relation:
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    type: uses
  toolType:
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  topic:
  - term: Genetics
    uri: http://edamontology.org/topic_3053
  validated: 1
  version:
  - '1'
- accessibility: null
  additionDate: '2015-01-29T15:47:59Z'
  biotoolsCURIE: biotools:ensembl_genomes_metazoa_blast
  biotoolsID: ensembl_genomes_metazoa_blast
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  - Ensembl Genomes
  - EBI Tools
  confidence_flag: null
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    typeRole:
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    url: null
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    name: EMBL-EBI
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    url: null
  - email: helpdesk@ensemblgenomes.org
    fundrefid: null
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  - email: eg-webteam@ebi.ac.uk
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    name: Ensembl Genomes webteam
    note: null
    orcidid: null
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    typeEntity: Person
    typeRole:
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    url: null
  description: Searches Ensembl Metazoa sequences using Exonerate.
  documentation:
  - note: null
    type:
    - Terms of use
    url: http://www.ebi.ac.uk/about/terms-of-use
  - note: null
    type:
    - General
    url: http://metazoa.ensembl.org/info/website/help/index.html
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    input:
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    note: null
    operation:
    - term: Sequence similarity search
      uri: http://edamontology.org/operation_0346
    output:
    - data:
        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format: []
    - data:
        term: Sequence search results
        uri: http://edamontology.org/data_0857
      format: []
  homepage: http://metazoa.ensembl.org/Multi/blastview
  homepage_status: 0
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  lastUpdate: '2024-11-25T14:07:17.756843Z'
  license: null
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  name: Ensembl Genomes Metazoa Blast
  operatingSystem:
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  owner: EMBL-EBI
  publication:
  - doi: 10.1093/nar/gkv1157
    metadata:
      abstract: The Ensembl project (http://www.ensembl.org) is a system for genome
        annotation, analysis, storage and dissemination designed to facilitate the
        access of genomic annotation from chordates and key model organisms. It provides
        access to data from 87 species across our main and early access Pre! websites.
        This year we introduced three newly annotated species and released numerous
        updates across our supported species with a concentration on data for the
        latest genome assemblies of human, mouse, zebrafish and rat. We also provided
        two data updates for the previous human assembly, GRCh37, through a dedicated
        website (http://grch37.ensembl.org). Our tools, in particular the VEP, have
        been improved significantly through integration of additional third party
        data. REST is now capable of larger-scale analysis and our regulatory data
        BioMart can deliver faster results. The website is now capable of displaying
        long-range interactions such as those found in cis-regulated datasets. Finally
        we have launched a website optimized for mobile devices providing views of
        genes, variants and phenotypes. Our data is made available without restriction
        and all code is available from our GitHub organization site (http://github.com/Ensembl)
        under an Apache 2.0 license.
      authors:
      - name: Yates A.
      - name: Akanni W.
      - name: Amode M.R.
      - name: Barrell D.
      - name: Billis K.
      - name: Carvalho-Silva D.
      - name: Cummins C.
      - name: Clapham P.
      - name: Fitzgerald S.
      - name: Gil L.
      - name: Giron C.G.
      - name: Gordon L.
      - name: Hourlier T.
      - name: Hunt S.E.
      - name: Janacek S.H.
      - name: Johnson N.
      - name: Juettemann T.
      - name: Keenan S.
      - name: Lavidas I.
      - name: Martin F.J.
      - name: Maurel T.
      - name: McLaren W.
      - name: Murphy D.N.
      - name: Nag R.
      - name: Nuhn M.
      - name: Parker A.
      - name: Patricio M.
      - name: Pignatelli M.
      - name: Rahtz M.
      - name: Riat H.S.
      - name: Sheppard D.
      - name: Taylor K.
      - name: Thormann A.
      - name: Vullo A.
      - name: Wilder S.P.
      - name: Zadissa A.
      - name: Birney E.
      - name: Harrow J.
      - name: Muffato M.
      - name: Perry E.
      - name: Ruffier M.
      - name: Spudich G.
      - name: Trevanion S.J.
      - name: Cunningham F.
      - name: Aken B.L.
      - name: Zerbino D.R.
      - name: Flicek P.
      citationCount: 1097
      date: '2016-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: Ensembl 2016
    note: null
    pmcid: PMC4702834
    pmid: '26687719'
    type:
    - Other
    version: null
  relation:
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  validated: 0
  version:
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- accessibility: null
  additionDate: '2015-01-29T15:47:59Z'
  biotoolsCURIE: biotools:ensembl_genomes_plants_blast
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    name: null
    note: null
    orcidid: null
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    typeRole:
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    url: null
  - email: eg-webteam@ebi.ac.uk
    fundrefid: null
    gridid: null
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    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
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    url: null
  description: Search Ensembl Plants sequences with WU-BLAST.
  documentation:
  - note: null
    type:
    - Terms of use
    url: http://www.ebi.ac.uk/about/terms-of-use
  - note: null
    type:
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    url: http://plants.ensembl.org/info/website/help/index.html
  download: []
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  function:
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    input:
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    note: null
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    metadata:
      abstract: The Ensembl project (http://www.ensembl.org) is a system for genome
        annotation, analysis, storage and dissemination designed to facilitate the
        access of genomic annotation from chordates and key model organisms. It provides
        access to data from 87 species across our main and early access Pre! websites.
        This year we introduced three newly annotated species and released numerous
        updates across our supported species with a concentration on data for the
        latest genome assemblies of human, mouse, zebrafish and rat. We also provided
        two data updates for the previous human assembly, GRCh37, through a dedicated
        website (http://grch37.ensembl.org). Our tools, in particular the VEP, have
        been improved significantly through integration of additional third party
        data. REST is now capable of larger-scale analysis and our regulatory data
        BioMart can deliver faster results. The website is now capable of displaying
        long-range interactions such as those found in cis-regulated datasets. Finally
        we have launched a website optimized for mobile devices providing views of
        genes, variants and phenotypes. Our data is made available without restriction
        and all code is available from our GitHub organization site (http://github.com/Ensembl)
        under an Apache 2.0 license.
      authors:
      - name: Yates A.
      - name: Akanni W.
      - name: Amode M.R.
      - name: Barrell D.
      - name: Billis K.
      - name: Carvalho-Silva D.
      - name: Cummins C.
      - name: Clapham P.
      - name: Fitzgerald S.
      - name: Gil L.
      - name: Giron C.G.
      - name: Gordon L.
      - name: Hourlier T.
      - name: Hunt S.E.
      - name: Janacek S.H.
      - name: Johnson N.
      - name: Juettemann T.
      - name: Keenan S.
      - name: Lavidas I.
      - name: Martin F.J.
      - name: Maurel T.
      - name: McLaren W.
      - name: Murphy D.N.
      - name: Nag R.
      - name: Nuhn M.
      - name: Parker A.
      - name: Patricio M.
      - name: Pignatelli M.
      - name: Rahtz M.
      - name: Riat H.S.
      - name: Sheppard D.
      - name: Taylor K.
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      - name: Hadi-Saljoqi S.
      - name: Sasorith S.
      - name: Lefranc G.
      - name: Kossida S.
      citationCount: 402
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      journal: Nucleic Acids Research
      title: IMGT R, the international ImMunoGeneTics information system R 25 years
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        proteins of the IgSF and MhSF superfamilies. IMGT is built on the IMGTONTOLOGY
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        IMGT unique numbering and IMGT Colliers de Perles (numerotation). IMGTR comprises
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      - name: Giudicelli V.
      - name: Duroux P.
      - name: Jabado-Michaloud J.
      - name: Folch G.
      - name: Aouinti S.
      - name: Carillon E.
      - name: Duvergey H.
      - name: Houles A.
      - name: Paysan-Lafosse T.
      - name: Hadi-Saljoqi S.
      - name: Sasorith S.
      - name: Lefranc G.
      - name: Kossida S.
      citationCount: 402
      date: '2015-01-28T00:00:00Z'
      journal: Nucleic Acids Research
      title: IMGT R, the international ImMunoGeneTics information system R 25 years
        on
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    metadata:
      abstract: IMGT, the international ImMunoGeneTics information system® (http://imgt.cines.fr),
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        AIDS, leukemias, lymphomas, myelomas), veterinary research, genome diversity
        and genome evolution studies of the adaptive immune responses, biotechnology
        related to antibody engineering (scFv, phage displays, combinatorial libraries)
        and therapeutical approaches (grafts, immunotherapy). IMGT is freely available
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      authors:
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      - name: Giudicelli V.
      - name: Ginestoux C.
      - name: Bosc N.
      - name: Folch G.
      - name: Guiraudou D.
      - name: Jabado-Michaloud J.
      - name: Magris S.
      - name: Scaviner D.
      - name: Thouvenin V.
      - name: Combres K.
      - name: Girod D.
      - name: Jeanjean S.
      - name: Protat C.
      - name: Monod M.Y.
      - name: Duprat E.
      - name: Kaas Q.
      - name: Pommie C.
      - name: Chaume D.
      - name: Lefranc G.
      citationCount: 91
      date: '2004-06-14T00:00:00Z'
      journal: In Silico Biology
      title: IMGT-ontology for immunogenetics and immunoinformatics
    note: null
    pmcid: null
    pmid: '15089751'
    type: []
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  - doi: null
    metadata:
      abstract: IMGT, the international ImMunoGeneTics information system® (http://imgt.cines.fr),
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        knowledge resource specialized in immunoglobulins (IG), T cell receptors (TR),
        major histocompatibility complex (MHC) of human and other vertebrates, and
        related proteins of the immune system (RPI) which belong to the immunoglobulin
        superfamily (IgSF) and MHC superfamily (MhcSF). IMGT provides a common access
        to standardized data from genome, proteome, genetics and three-dimensional
        structures. The accuracy and the consistency of IMGT data are based on IMGT-ONTOLOGY,
        a semantic specification of terms to be used in immunogenetics and immunoinformatics.
        IMGT-ONTOLOGY has been formalized using XML Schema (IMGT-ML) for interoperability
        with other information systems. We are developing Web services to automatically
        query IMGT databases and tools. This is the first step towards IMGT-Choreography
        which will trigger and coordinate dynamic interactions between IMGT Web services
        to process complex significant biological and clinical requests. IMGT-Choreography
        will further increase the IMGT leadership in immunogenetics and immunoinformatics
        for medical research (repertoire analysis of the IG antibody recognition sites
        and of the TR recognition sites in autoimmune and infectious diseases, AIDS,
        leukemias, lymphomas, myelomas), veterinary research (IG and TR repertoires
        in farm and wild life species), genome diversity and genome evolution studies
        of the adaptive immune responses, biotechnology related to antibody engineering
        (single chain Fragment variable (scFv), phage displays, combinatorial libraries,
        chimeric, humanized and human antibodies), diagnostics (detection and follow-up
        of residual diseases) and therapeutical approaches (grafts, immunotherapy,
        vaccinology). IMGT is freely available at http://imgt.cines.fr. © 2005 IOS
        Press. All rights reserved.
      authors:
      - name: Lefranc M.-P.
      - name: Clement O.
      - name: Kaas Q.
      - name: Duprat E.
      - name: Chastellan P.
      - name: Coelho I.
      - name: Combres K.
      - name: Ginestoux C.
      - name: Giudicelli V.
      - name: Chaume D.
      - name: Lefranc G.
      citationCount: 74
      date: '2005-06-13T00:00:00Z'
      journal: In Silico Biology
      title: IMGT-Choreography for immunogenetics and immunoinformatics
    note: null
    pmcid: null
    pmid: '15972004'
    type: []
    version: null
  - doi: 10.1093/nar/gku1056
    metadata:
      abstract: IMGT, the international ImMunoGeneTics information system (http://www.imgt.org)
        is the global reference in immunogenetics and immunoinformatics. By its creation
        in 1989 by Marie-Paule Lefranc (Université de Montpellier and CNRS), IMGT
        marked the advent of immunoinformatics, which emerged at the interface between
        immunogenetics and bioinformatics. IMGT is specialized in the immunoglobulins
        (IG) or antibodies, T cell receptors (TR), major histocompatibility (MH) and
        proteins of the IgSF and MhSF superfamilies. IMGT is built on the IMGTONTOLOGY
        axioms and concepts, which bridged the gap between genes, sequences and 3D
        structures. The concepts include the IMGTR standardized keywords (identification),
        IMGTR standardized labels (description), IMGTR standardized nomenclature (classification),
        IMGT unique numbering and IMGT Colliers de Perles (numerotation). IMGTR comprises
        7 databases, 17 online tools and 15 000 pages of web resources, and provides
        a high-quality and integrated system for analysis of the genomic and expressed
        IG and TR repertoire of the adaptive immune responses, including NGS high-throughput
        data. Tools and databases are used in basic, veterinary and medical research,
        in clinical applications (mutation analysis in leukemia and lymphoma) and
        in antibody engineering and humanization. The IMGT/mAb-DB interface was developed
        for therapeutic antibodies and fusion proteins for immunological applications
        (FPIA). IMGTR is freely available at http://www.imgt.org.
      authors:
      - name: Lefranc M.-P.
      - name: Giudicelli V.
      - name: Duroux P.
      - name: Jabado-Michaloud J.
      - name: Folch G.
      - name: Aouinti S.
      - name: Carillon E.
      - name: Duvergey H.
      - name: Houles A.
      - name: Paysan-Lafosse T.
      - name: Hadi-Saljoqi S.
      - name: Sasorith S.
      - name: Lefranc G.
      - name: Kossida S.
      citationCount: 402
      date: '2015-01-28T00:00:00Z'
      journal: Nucleic Acids Research
      title: IMGT R, the international ImMunoGeneTics information system R 25 years
        on
    note: null
    pmcid: PMC4383898
    pmid: '25378316'
    type: []
    version: null
  relation:
  - biotoolsID: imgt
    type: includedIn
  toolType:
  - Web application
  topic:
  - term: Immunology
    uri: http://edamontology.org/topic_0804
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  validated: 0
  version: []
- accessibility: null
  additionDate: '2019-12-18T08:05:57Z'
  biotoolsCURIE: biotools:IMGT_JunctionAnalysis
  biotoolsID: IMGT_JunctionAnalysis
  collectionID: []
  confidence_flag: null
  cost: Free of charge (with restrictions)
  credit:
  - email: veronique.giudicelli@igh.cnrs.fr
    fundrefid: null
    gridid: null
    name: Véronique Giudicelli
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: patrice.duroux@igh.cnrs.fr
    fundrefid: null
    gridid: null
    name: Patrice Duroux
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: marie-paule.lefranc@igh.cnrs.fr
    fundrefid: null
    gridid: null
    name: Marie-Paule Lefranc
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: sofia.kossida@igh.cnrs.fr
    fundrefid: null
    gridid: null
    name: Sofia Kossida
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: 'IMGT/JunctionAnalysis is the IMGT® tool for the analysis of the nucleotide
    sequences of the V-J and V-D-J junctions of the variable domains of the immunoglobulins
    (IG) or antibodies and T cell receptors (TR).

    Analysis is based on the IMGT-ONTOLOGY concepts.'
  documentation:
  - note: null
    type:
    - User manual
    url: http://www.imgt.org/IMGT_jcta/user_guide
  download: []
  editPermission:
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    input:
    - data:
        term: Nucleic acid sequence
        uri: http://edamontology.org/data_2977
      format:
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        uri: http://edamontology.org/format_2200
    note: null
    operation:
    - term: Sequence alignment analysis (conservation)
      uri: http://edamontology.org/operation_0448
    - term: Nucleic acid sequence analysis
      uri: http://edamontology.org/operation_2478
    - term: Sequence alignment
      uri: http://edamontology.org/operation_0292
    output:
    - data:
        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
    - data:
        term: Sequence alignment report
        uri: http://edamontology.org/data_0867
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
  homepage: http://www.imgt.org/IMGT_jcta
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2024-11-25T13:59:28.822742Z'
  license: null
  link: []
  maturity: Mature
  name: IMGT JunctionAnalysis
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: vgiudicelli
  publication:
  - doi: 10.1093/bioinformatics/bth945
    metadata:
      abstract: 'Motivation: To create the enormous diversity of 1012 immunoglobulins
        (IG) and T cell receptors (TR) per individual, very complex mechanisms occur
        at the DNA level: the combinatorial diversity results from the junction of
        the variable (V), diversity (D) and joining (J) genes; the N-diversity represents
        the addition at random of nucleotides not encoded in the genome; and somatic
        hypermutations occur in IG rearranged sequences. The accurate annotation of
        the junction between V, D, J genes in rearranged IG and TR sequences represents
        therefore a huge challenge by its uniqueness and complexity. We developed
        IMGT/JunctionAnalysis to analyse automatically in detail the IG and TR junctions,
        according to the IMGT Scientific chart rules, based on the IMGT-ONTOLOGY concepts.
        Results: IMGT/JunctionAnalysis is the first tool forthe detailed analysis
        of the IG and TR complex V-J and V-D-J JUNCTION(s). It delimits, at the nucleotide
        level, the genes resulting from the combinatorial diversity. It identifies
        accurately the D genes in the junctions of IG heavy (IGH), TR beta (TRB) and
        delta (TRD) chains. It delimits the palindromic P-REGION(s) and the N-REGION(s)
        resulting from the N-diversity. It evaluates the number of somatic hypermutations
        for each gene, within the JUNCTION. IMGT/JunctionAnalysis is capable of analysing,
        in a single run, an unlimited number of junctions from the same species (currently
        human or mouse) and from the same locus. Availability: IMGT/JunctionAnalysis
        is available from the IMGT Home page at http://imgt.cines.fr. © Oxford University
        Press 2004; all rights reserved.'
      authors:
      - name: Monod M.Y.
      - name: Giudicelli V.
      - name: Chaume D.
      - name: Lefranc M.-P.
      citationCount: 272
      date: '2004-01-01T00:00:00Z'
      journal: Bioinformatics
      title: 'IMGT/JunctionAnalysis: The first tool for the analysis of the immunoglobulin
        and T cell receptor complex V-J and V-D-J JUNCTIONs'
    note: null
    pmcid: null
    pmid: '15262823'
    type: []
    version: null
  - doi: 10.1101/pdb.prot5634
    metadata:
      abstract: ''
      authors:
      - name: Giudicelli V.
      - name: Lefranc M.-P.
      citationCount: 89
      date: '2011-06-01T00:00:00Z'
      journal: Cold Spring Harbor Protocols
      title: 'IMGT/junctionanalysis: IMGT standardized analysis of the V-J and V-D-J
        junctions of the rearranged immunoglobulins (IG) and T cell receptors (TR)'
    note: null
    pmcid: null
    pmid: '21632777'
    type: []
    version: null
  - doi: 10.1093/nar/gku1056
    metadata:
      abstract: IMGT, the international ImMunoGeneTics information system (http://www.imgt.org)
        is the global reference in immunogenetics and immunoinformatics. By its creation
        in 1989 by Marie-Paule Lefranc (Université de Montpellier and CNRS), IMGT
        marked the advent of immunoinformatics, which emerged at the interface between
        immunogenetics and bioinformatics. IMGT is specialized in the immunoglobulins
        (IG) or antibodies, T cell receptors (TR), major histocompatibility (MH) and
        proteins of the IgSF and MhSF superfamilies. IMGT is built on the IMGTONTOLOGY
        axioms and concepts, which bridged the gap between genes, sequences and 3D
        structures. The concepts include the IMGTR standardized keywords (identification),
        IMGTR standardized labels (description), IMGTR standardized nomenclature (classification),
        IMGT unique numbering and IMGT Colliers de Perles (numerotation). IMGTR comprises
        7 databases, 17 online tools and 15 000 pages of web resources, and provides
        a high-quality and integrated system for analysis of the genomic and expressed
        IG and TR repertoire of the adaptive immune responses, including NGS high-throughput
        data. Tools and databases are used in basic, veterinary and medical research,
        in clinical applications (mutation analysis in leukemia and lymphoma) and
        in antibody engineering and humanization. The IMGT/mAb-DB interface was developed
        for therapeutic antibodies and fusion proteins for immunological applications
        (FPIA). IMGTR is freely available at http://www.imgt.org.
      authors:
      - name: Lefranc M.-P.
      - name: Giudicelli V.
      - name: Duroux P.
      - name: Jabado-Michaloud J.
      - name: Folch G.
      - name: Aouinti S.
      - name: Carillon E.
      - name: Duvergey H.
      - name: Houles A.
      - name: Paysan-Lafosse T.
      - name: Hadi-Saljoqi S.
      - name: Sasorith S.
      - name: Lefranc G.
      - name: Kossida S.
      citationCount: 402
      date: '2015-01-28T00:00:00Z'
      journal: Nucleic Acids Research
      title: IMGT R, the international ImMunoGeneTics information system R 25 years
        on
    note: null
    pmcid: PMC4383898
    pmid: '25378316'
    type: []
    version: null
  relation:
  - biotoolsID: imgt
    type: includedIn
  toolType:
  - Web application
  topic:
  - term: Immunoinformatics
    uri: http://edamontology.org/topic_3948
  - term: Immunogenetics
    uri: http://edamontology.org/topic_3930
  validated: 0
  version: []
- accessibility: null
  additionDate: '2017-05-01T13:19:16Z'
  biotoolsCURIE: biotools:imgt_v-quest
  biotoolsID: imgt_v-quest
  collectionID: []
  confidence_flag: null
  cost: Free of charge (with restrictions)
  credit:
  - email: Marie-Paule.Lefranc@igh.cnrs.fr
    fundrefid: null
    gridid: null
    name: Marie-Paule Lefranc
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: veronique.giudicelli@igh.cnrs.fr
    fundrefid: null
    gridid: null
    name: Véronique Giudicelli
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: patrice.duroux@igh.cnrs.fr
    fundrefid: null
    gridid: null
    name: Patrice Duroux
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: sofia.kossida@igh.cnrs.fr
    fundrefid: null
    gridid: null
    name: Sofia Kossida
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: 'IMGT/V-QUEST is the IMGT® tool for nucleotide sequence alignment and
    analysis of immunoglobulin (IG) or antibody and T cell receptor (TR) variable
    domains, integrates IMGT/JunctionAnalysis, IMGT/Automat and IMGT/Collier-de-Perles.

    Analysis is based on the IMGT-ONTOLOGY concepts.'
  documentation:
  - note: null
    type:
    - User manual
    url: http://www.imgt.org/IMGT_vquest/user_guide
  - note: IMGT/V-QUEST program versions
    type:
    - Release notes
    url: http://www.imgt.org/IMGT_vquest/program_versions
  - note: IMGT/V-QUEST reference directory releases
    type:
    - Release notes
    url: http://www.imgt.org/IMGT_vquest/data_releases
  download: []
  editPermission:
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    - Shengli
    - vgiudicelli
    - skossida
    - pduroux
    - Joumana
    - geraldine.folch
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Nucleic acid sequence
        uri: http://edamontology.org/data_2977
      format:
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        uri: http://edamontology.org/format_1929
    note: null
    operation:
    - term: Sequence trimming
      uri: http://edamontology.org/operation_3192
    - term: Sequence alignment analysis
      uri: http://edamontology.org/operation_0258
    - term: Sequence alignment
      uri: http://edamontology.org/operation_0292
    - term: Sequence alignment analysis (conservation)
      uri: http://edamontology.org/operation_0448
    output:
    - data:
        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
      - term: Textual format
        uri: http://edamontology.org/format_2330
    - data:
        term: Sequence features
        uri: http://edamontology.org/data_1255
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
      - term: Textual format
        uri: http://edamontology.org/format_2330
    - data:
        term: Sequence report
        uri: http://edamontology.org/data_2955
      format:
      - term: xlsx
        uri: http://edamontology.org/format_3620
      - term: HTML
        uri: http://edamontology.org/format_2331
      - term: Textual format
        uri: http://edamontology.org/format_2330
  homepage: http://www.imgt.org/IMGT_vquest
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2024-11-25T13:59:09.724903Z'
  license: null
  link: []
  maturity: Mature
  name: IMGT V-QUEST
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: vgiudicelli
  publication:
  - doi: 10.1093/nar/gkn316
    metadata:
      abstract: IMGT/V-QUEST is the highly customized and integrated system for the
        standardized analysis of the immunoglobulin (IG) and T cell receptor (TR)
        rearranged nucleotide sequences. IMGT/V-QUEST identifies the variable (V),
        diversity (D) and joining (J) genes and alleles by alignment with the germline
        IG and TR gene and allele sequences of the IMGT reference directory. New functionalities
        were added through a complete rewrite in Java. IMGT/V-QUEST analyses batches
        of sequences (up to 50) in a single run. IMGT/V-QUEST describes the V-REGION
        mutations and identifies the hot spot positions in the closest germline V
        gene. IMGT/V-QUEST can detect insertions and deletions in the submitted sequences
        by reference to the IMGT unique numbering. IMGT/V-QUEST integrates IMGT/JunctionAnalysis
        for a detailed analysis of the V-J and V-D-J junctions, and IMGT/Automat for
        a full V-J- and V-D-J-REGION annotation. IMGT/V-QUEST displays, in 'Detailed
        view', the results and alignments for each submitted sequence individually
        and, in 'Synthesis view', the alignments of the sequences that, in a given
        run, express the same V gene and allele. The 'Advanced parameters' allow to
        modify default parameters used by IMGT/V-QUEST and IMGT/JunctionAnalysis according
        to the users' interest. IMGT/V-QUEST is freely available for academic research
        at http://imgt.cines.fr.
      authors:
      - name: Brochet X.
      - name: Lefranc M.P.
      - name: Giudicelli V.
      citationCount: 942
      date: '2008-01-01T00:00:00Z'
      journal: Nucleic acids research
      title: 'IMGT/V-QUEST: the highly customized and integrated system for IG and
        TR standardized V-J and V-D-J sequence analysis.'
    note: null
    pmcid: PMC2447746
    pmid: '18503082'
    type: []
    version: null
  - doi: 10.1093/nar/gkh412
    metadata:
      abstract: 'IMGT/V-QUEST, for ''V-QUEry and STandardization'', is an integrated
        software program which analyses the immunoglobulin (IG) and T cell receptor
        (TR) rearranged nucleotide sequences. The extraordinary diversity of the IG
        and TR repertoires (1012 antibodies and 1012 TR per individual) results from
        several mechanisms at the DNA level: the combinatorial diversity of the variable
        (V), diversity (D) and joining (J) genes, the N-diversity and, for IG, the
        somatic mutations. IMGT/V-QUEST identifies the V, D and J genes and alleles
        by alignment with the germline IG and TR gene and allele sequences of the
        IMGT reference directory. IMGT/V-QUEST delimits the structurally important
        features, frameworks and complementarity-determining regions (the last of
        these forming the antigen binding site), on the basis of the IMGT unique numbering.
        The tool localizes the somatic mutations of the IG rearranged sequences. IMGT/V-QUEST
        also dynamically displays a graphical two-dimensional representation, or IMGT
        Collier de Peries, of the IG and TR variable regions. Moreover, IMGT/V-QUEST
        can interact with IMGT/JunctionAnalysis for the detailed description of the
        V-J and V-D-J junctions, and with IMGT/PhyloGene for the construction of phylogenetic
        trees. IMGT/V-QUEST is currently available for human and mouse, and partly
        for non-human primates, sheep, chondrichthyes and teleostei. IMGT/V-QUEST
        is freely available at http://imgt.cines.fri. © Oxford University Press 2004;
        all rights reserved.'
      authors:
      - name: Giudicelli V.
      - name: Chaume D.
      - name: Lefranc M.-P.
      citationCount: 253
      date: '2004-07-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: IMGT/V-QUEST, an integrated software program for immunoglobulin and T
        cell receptor V-J and V-D-J rearrangement analysis
    note: null
    pmcid: PMC441550
    pmid: '15215425'
    type: []
    version: null
  - doi: 10.1101/pdb.prot5633
    metadata:
      abstract: ''
      authors:
      - name: Giudicelli V.
      - name: Brochet X.
      - name: Lefranc M.-P.
      citationCount: 301
      date: '2011-06-01T00:00:00Z'
      journal: Cold Spring Harbor Protocols
      title: 'IMGT/V-QUEST: IMGT standardized analysis of the immunoglobulin (IG)
        and T cell receptor (TR) nucleotide sequences'
    note: null
    pmcid: null
    pmid: '21632778'
    type: []
    version: null
  - doi: 10.1093/nar/gku1056
    metadata:
      abstract: IMGT, the international ImMunoGeneTics information system (http://www.imgt.org)
        is the global reference in immunogenetics and immunoinformatics. By its creation
        in 1989 by Marie-Paule Lefranc (Université de Montpellier and CNRS), IMGT
        marked the advent of immunoinformatics, which emerged at the interface between
        immunogenetics and bioinformatics. IMGT is specialized in the immunoglobulins
        (IG) or antibodies, T cell receptors (TR), major histocompatibility (MH) and
        proteins of the IgSF and MhSF superfamilies. IMGT is built on the IMGTONTOLOGY
        axioms and concepts, which bridged the gap between genes, sequences and 3D
        structures. The concepts include the IMGTR standardized keywords (identification),
        IMGTR standardized labels (description), IMGTR standardized nomenclature (classification),
        IMGT unique numbering and IMGT Colliers de Perles (numerotation). IMGTR comprises
        7 databases, 17 online tools and 15 000 pages of web resources, and provides
        a high-quality and integrated system for analysis of the genomic and expressed
        IG and TR repertoire of the adaptive immune responses, including NGS high-throughput
        data. Tools and databases are used in basic, veterinary and medical research,
        in clinical applications (mutation analysis in leukemia and lymphoma) and
        in antibody engineering and humanization. The IMGT/mAb-DB interface was developed
        for therapeutic antibodies and fusion proteins for immunological applications
        (FPIA). IMGTR is freely available at http://www.imgt.org.
      authors:
      - name: Lefranc M.-P.
      - name: Giudicelli V.
      - name: Duroux P.
      - name: Jabado-Michaloud J.
      - name: Folch G.
      - name: Aouinti S.
      - name: Carillon E.
      - name: Duvergey H.
      - name: Houles A.
      - name: Paysan-Lafosse T.
      - name: Hadi-Saljoqi S.
      - name: Sasorith S.
      - name: Lefranc G.
      - name: Kossida S.
      citationCount: 402
      date: '2015-01-28T00:00:00Z'
      journal: Nucleic Acids Research
      title: IMGT R, the international ImMunoGeneTics information system R 25 years
        on
    note: null
    pmcid: PMC4383898
    pmid: '25378316'
    type: []
    version: null
  relation:
  - biotoolsID: imgt
    type: includedIn
  toolType:
  - Web application
  topic:
  - term: Immunoinformatics
    uri: http://edamontology.org/topic_3948
  - term: Immunogenetics
    uri: http://edamontology.org/topic_3930
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  - term: Sequencing
    uri: http://edamontology.org/topic_3168
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-03-24T09:34:04Z'
  biotoolsCURIE: biotools:clustalw
  biotoolsID: clustalw
  collectionID:
  - clustal
  confidence_flag: null
  cost: null
  credit:
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    fundrefid: null
    gridid: null
    name: Clustal helpdesk
    note: null
    orcidid: null
    rorid: null
    typeEntity: Division
    typeRole:
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    url: null
  description: Multiple sequence alignment software. Old deprecated versions. Even
    older versions were CLUSTAL and CLUSTAL V (ClustalV).
  documentation: []
  download:
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    type: Downloads page
    url: http://www.clustal.org/download/1.X/ftp-igbmc.u-strasbg.fr/pub/
    version: 1.8 - 1.83
  editPermission:
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  elixir_badge: 0
  function:
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    input:
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      format:
      - term: FASTA
        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/download/1.X/ftp-igbmc.u-strasbg.fr/pub/
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T13:59:02.403313Z'
  license: null
  link: []
  maturity: Legacy
  name: Clustal 1.8 (Clustal W, Clustal X)
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: ELIXIR-EE
  publication:
  - doi: 10.1093/nar/22.22.4673
    metadata:
      abstract: The sensitivity of the commonly used progressive multiple sequence
        alignment method has been greatly improved for the alignment of divergent
        protein sequences. Firstly, individual weights are assigned to each sequence
        in a partial alignment in order to downweight near-duplicate sequences and
        up-weight the most divergent ones. Secondly, amino acid substitution matrices
        are varied at different alignment stages according to the divergence of the
        sequences to be aligned. Thirdly, residue-specific gap penalties and locally
        reduced gap penalties in hydrophilic regions encourage new gaps in potential
        loop regions rather than regular secondary structure. Fourthly, positions
        in early alignments where gaps have been opened receive locally reduced gap
        penalties to encourage the opening up of new gaps at these positions. These
        modifications are incorporated into a new program, CLUSTAL W which is freely
        available. © 1994 Oxford University Press.
      authors:
      - name: Thompson J.D.
      - name: Higgins D.G.
      - name: Gibson T.J.
      citationCount: 58068
      date: '1994-11-11T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'CLUSTAL W: Improving the sensitivity of progressive multiple sequence
        alignment through sequence weighting, position-specific gap penalties and
        weight matrix choice'
    note: Historical publication on CLUSTAL W. Open access to PDF only.
    pmcid: PMC308517
    pmid: '7984417'
    type:
    - Primary
    version: historical CLUSTAL W
  - doi: 10.1093/nar/25.24.4876
    metadata:
      abstract: 'CLUSTAL X is a new windows interface for the widely-used progressive
        multiple sequence alignment program CLUSTAL W. The new system is easy to use,
        providing an integrated system for performing multiple sequence and profile
        alignments and analysing the results. CLUSTAL X displays the sequence alignment
        in a window on the screen. A versatile sequence colouring scheme allows the
        user to highlight conserved features in the alignment. Pull-down menus provide
        all the options required for traditional multiple sequence and profile alignment.
        New features include: the ability to cut-and-paste sequences to change the
        order of the alignment, selection of a subset of the sequences to be realigned,
        and selection of a sub-range of the alignment to be realigned and inserted
        back into the original alignment. Alignment quality analysis can be performed
        and low-scoring segments or exceptional residues can be highlighted. Quality
        analysis and realignment of selected residue ranges provide the user with
        a powerful tool to improve and refine difficult alignments and to trap errors
        in input sequences. CLUSTAL X has been compiled on SUN Solaris, IRIX5.3 on
        Silicon Graphics, Digital UNIX on DECstations, Microsoft Windows (32 bit)
        for PCs, Linux ELF for x86 PCs, and Macintosh PowerMac.'
      authors:
      - name: Thompson J.D.
      - name: Gibson T.J.
      - name: Plewniak F.
      - name: Jeanmougin F.
      - name: Higgins D.G.
      citationCount: 36458
      date: '1997-12-15T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'The CLUSTAL X windows interface: Flexible strategies for multiple sequence
        alignment aided by quality analysis tools'
    note: Historical publication on CLUSTAL X. Open access.
    pmcid: PMC147148
    pmid: '9396791'
    type:
    - Primary
    version: historical CLUSTAL X
  - doi: 10.1093/nar/gkg500
    metadata:
      abstract: The Clustal series of programs are widely used in molecular biology
        for the multiple alignment of both nucleic acid and protein sequences and
        for preparing phylogenetic trees. The popularity of the programs depends on
        a number of factors, including not only the accuracy of the results, but also
        the robustness, portability and user-friendliness of the programs. New features
        include NEXUS and FASTA format output, printing range numbers and faster tree
        calculation. Although, Clustal was originally developed to run on a local
        computer, numerous Web servers have been set up, notably at the EBI (European
        Bioinformatics Institute) (http://www.ebi.ac.uk/clustalw/).
      authors:
      - name: Chenna R.
      - name: Sugawara H.
      - name: Koike T.
      - name: Lopez R.
      - name: Gibson T.J.
      - name: Higgins D.G.
      - name: Thompson J.D.
      citationCount: 4217
      date: '2003-07-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: Multiple sequence alignment with the Clustal series of programs
    note: Short overview article, with some new features of Clustal, Clustal X, and
      other associated software nad services. Open access.
    pmcid: PMC168907
    pmid: '12824352'
    type:
    - Primary
    version: '1.83'
  - doi: 10.1093/bioinformatics/8.2.189
    metadata:
      abstract: The CLUSTAL package of multiple sequence alignment programs has been
        completely rewritten and many new features added. The new software is a single
        program called CLUSTAL V, which is written in C and can be used on standard
        C compiler. The main new features are the ability to store and reuse old alignments
        and the ability to calculate phylogenetic trees after alignment. The program
        is simple to use, completely menu driven and on-line help is provided. © 1992
        Oxford University Press.
      authors:
      - name: Higgins D.G.
      - name: Bleasby A.J.
      - name: Fuchs R.
      citationCount: 2572
      date: '1992-04-01T00:00:00Z'
      journal: Bioinformatics
      title: 'CLUSTAL V: Improved software for multiple sequence alignment'
    note: Historical publication on CLUSTAL. Closed access.
    pmcid: null
    pmid: '1591615'
    type:
    - Other
    version: historical CLUSTAL
  - doi: 10.1016/0378-1119(88)90330-7
    metadata:
      abstract: An approach for performing multiple alignments of large numbers of
        amino acid or nucleotide sequences is described. The method is based on first
        deriving a phylogenetic tree from a matrix of all pairwise sequence similarity
        scores, obtained using a fast pairwise alignment algorithm. Then the multiple
        alignment is achieved from a series of pairwise alignments of clusters of
        sequences, following the order of branching in the tree. The method is sufficiently
        fast and economical with memory to be easily implemented on a microcomputer,
        and yet the results obtained are comparable to those from packages requiring
        mainframe computer facilities. © 1988.
      authors:
      - name: Higgins D.G.
      - name: Sharp P.M.
      citationCount: 3024
      date: '1988-12-15T00:00:00Z'
      journal: Gene
      title: 'CLUSTAL: a package for performing multiple sequence alignment on a microcomputer'
    note: Historical publication on CLUSTAL. Closed access.
    pmcid: null
    pmid: null
    type:
    - Other
    version: historical CLUSTAL
  relation:
  - biotoolsID: clustal2
    type: hasNewVersion
  toolType:
  - Command-line tool
  - Desktop application
  topic:
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  validated: 1
  version:
  - 1.8 - 1.83
- accessibility: null
  additionDate: '2017-08-01T11:05:01Z'
  biotoolsCURIE: biotools:proteinsplus
  biotoolsID: proteinsplus
  collectionID:
  - de.NBI
  - COVID-19
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: University of Hamburg - Center for Bioinformatics
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: rarey-office@zbh.uni-hamburg.de
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: It supports various commonly required tasks of structure-based molecular
    modeling. It provides functionalities for structure quality assessment , hydrogen
    placement, the search for alternative conformations, the generation of 2D-interaction
    diagrams, protein-protein interface classification as well as automatic pocket
    detection and druggablity assessment.
  documentation:
  - note: null
    type:
    - General
    url: http://proteinsplus.zbh.uni-hamburg.de/help/index
  download: []
  editPermission:
    authors:
    - Bietz
    type: group
  elixirCommunity:
  - 3D-BioInfo
  elixirNode:
  - Germany
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein structure
        uri: http://edamontology.org/data_1460
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
    note: null
    operation:
    - term: Protein model validation
      uri: http://edamontology.org/operation_0321
    - term: Protein interaction analysis
      uri: http://edamontology.org/operation_2949
    - term: Structure visualisation
      uri: http://edamontology.org/operation_0570
    - term: Protein binding site prediction
      uri: http://edamontology.org/operation_2575
    - term: Protein structure analysis
      uri: http://edamontology.org/operation_2406
    - term: Structure database search
      uri: http://edamontology.org/operation_0339
    output:
    - data:
        term: Protein structure
        uri: http://edamontology.org/data_1460
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
    - data:
        term: Protein property
        uri: http://edamontology.org/data_0897
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
    - data:
        term: Protein structure image
        uri: http://edamontology.org/data_2992
      format:
      - term: PNG
        uri: http://edamontology.org/format_3603
      - term: SVG
        uri: http://edamontology.org/format_3604
      - term: PDF
        uri: http://edamontology.org/format_3508
    - data:
        term: Score
        uri: http://edamontology.org/data_1772
      format: []
    - data:
        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format:
      - term: protein
        uri: http://edamontology.org/format_1208
  homepage: http://proteinsplus.zbh.uni-hamburg.de
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T13:58:14.662890Z'
  license: null
  link: []
  maturity: null
  name: ProteinsPlus
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: stierand
  publication:
  - doi: 10.1093/nar/gkx333
    metadata:
      abstract: With currently more than 126 000 publicly available structures and
        an increasing growth rate, the Protein Data Bank constitutes a rich data source
        for structure-driven research in fields like drug discovery, crop science
        and biotechnology in general. Typical workflows in these areas involve manifold
        computational tools for the analysis and prediction of molecular functions.
        Here, we present the ProteinsPlus web server that offers a unified easy-to-use
        interface to a broad range of tools for the early phase of structure-based
        molecular modeling. This includes solutions for commonly required pre-processing
        tasks like structure quality assessment (EDIA), hydrogen placement (Protoss)
        and the search for alternative conformations (SIENA). Beyond that, it also
        addresses frequent problems as the generation of 2D-interaction diagrams (PoseView),
        protein-protein interface classification (HyPPI) as well as automatic pocket
        detection and druggablity assessment (DoGSiteScorer). The unified ProteinsPlus
        interface covering all featured approaches provides various facilities for
        intuitive input and result visualization, case-specific parameterization and
        download options for further processing. Moreover, its generalized workflow
        allows the user a quick familiarization with the different tools. ProteinsPlus
        also stores the calculated results temporarily for future request and thus
        facilitates convenient result communication and re-access.
      authors:
      - name: Fahrrolfes R.
      - name: Bietz S.
      - name: Flachsenberg F.
      - name: Meyder A.
      - name: Nittinger E.
      - name: Otto T.
      - name: Volkamer A.
      - name: Rarey M.
      citationCount: 167
      date: '2017-07-03T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'Proteins Plus: A web portal for structure analysis of macromolecules'
    note: null
    pmcid: PMC5570178
    pmid: '28472372'
    type:
    - Primary
    version: null
  - doi: 10.1093/nar/gkaa235
    metadata:
      abstract: 'Due to the increasing amount of publicly available protein structures
        searching, enriching and investigating these data still poses a challenging
        task. The ProteinsPlus web service (https://proteins.plus) offers a broad
        range of tools addressing these challenges. The web interface to the tool
        collection focusing on protein–ligand interactions has been geared towards
        easy and intuitive access to a large variety of functionality for life scientists.
        Since our last publication, the ProteinsPlus web service has been extended
        by additional services as well as it has undergone substantial infrastructural
        improvements. A keyword search functionality was added on the start page of
        ProteinsPlus enabling users to work on structures without knowing their PDB
        code. The tool collection has been augmented by three tools: StructureProfiler
        validates ligands and active sites using selection criteria of well-established
        protein–ligand benchmark data sets, WarPP places water molecules in the lig-
        and binding sites of a protein, and METALizer calculates, predicts and scores
        coordination geometries of metal ions based on surrounding complex atoms.
        Additionally, all tools provided by ProteinsPlus are available through a REST
        service enabling the automated integration in structure processing and modeling
        pipelines.'
      authors:
      - name: Schoning-Stierand K.
      - name: Diedrich K.
      - name: Fahrrolfes R.
      - name: Flachsenberg F.
      - name: Meyder A.
      - name: Nittinger E.
      - name: Steinegger R.
      - name: Rarey M.
      citationCount: 164
      date: '2020-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'ProteinsPlus: Interactive analysis of protein–ligand binding interfaces'
    note: null
    pmcid: PMC7319454
    pmid: '32297936'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Web service
  topic:
  - term: Structure analysis
    uri: http://edamontology.org/topic_0081
  - term: Protein binding sites
    uri: http://edamontology.org/topic_3534
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2016-12-19T14:28:04Z'
  biotoolsCURIE: biotools:setuppromoter
  biotoolsID: setuppromoter
  collectionID:
  - galaxyPasteur
  - Institut Pasteur
  confidence_flag: null
  cost: null
  credit:
  - email: galaxy@pasteur.fr
    fundrefid: null
    gridid: null
    name: Galaxy Support Team
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Builds a fasta file of sequences from a reference genome using promoter
    region coordinates.
  documentation:
  - note: null
    type:
    - General
    url: https://galaxy.pasteur.fr/root?tool_id=toolshed.pasteur.fr%2Frepos%2Ffmareuil%2Fpromoteur_tools%2Fsetuppromoter%2F1.0
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Data
        uri: http://edamontology.org/data_0006
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
    note: null
    operation:
    - term: Sequence assembly
      uri: http://edamontology.org/operation_0310
    output:
    - data:
        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
  homepage: https://galaxy.pasteur.fr/tool_runner?tool_id=toolshed.pasteur.fr/repos/fmareuil/promoteur_tools/setuppromoter/1.0
  homepage_status: 0
  language:
  - Perl
  lastUpdate: '2024-11-25T13:57:43.143503Z'
  license: null
  link:
  - note: null
    type:
    - Galaxy service
    url: https://galaxy.pasteur.fr/tool_runner?tool_id=toolshed.pasteur.fr/repos/fmareuil/promoteur_tools/setuppromoter/1.0
  maturity: Mature
  name: setuppromoter
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: hmenager
  publication:
  - doi: 10.1093/nar/gkw343
    metadata:
      abstract: High-throughput data production technologies, particularly ‘next-generation’
        DNA sequencing, have ushered in widespread and disruptive changes to biomedical
        research. Making sense of the large datasets produced by these technologies
        requires sophisticated statistical and computational methods, as well as substantial
        computational power. This has led to an acute crisis in life sciences, as
        researchers without informatics training attempt to perform computation-dependent
        analyses. Since 2005, the Galaxy project has worked to address this problem
        by providing a framework that makes advanced computational tools usable by
        non experts. Galaxy seeks to make data-intensive research more accessible,
        transparent and reproducible by providing a Web-based environment in which
        users can perform computational analyses and have all of the details automatically
        tracked for later inspection, publication, or reuse. In this report we highlight
        recently added features enabling biomedical analyses on a large scale.
      authors:
      - name: Afgan E.
      - name: Baker D.
      - name: van den Beek M.
      - name: Blankenberg D.
      - name: Bouvier D.
      - name: Cech M.
      - name: Chilton J.
      - name: Clements D.
      - name: Coraor N.
      - name: Eberhard C.
      - name: Gruning B.
      - name: Guerler A.
      - name: Hillman-Jackson J.
      - name: Kuster G.V.
      - name: Rasche E.
      - name: Soranzo N.
      - name: Turaga N.
      - name: Taylor J.
      - name: Nekrutenko A.
      - name: Goecks J.
      citationCount: 1410
      date: '2016-07-08T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'The Galaxy platform for accessible, reproducible and collaborative biomedical
        analyses: 2016 update'
    note: null
    pmcid: PMC4987906
    pmid: '27137889'
    type:
    - Other
    version: null
  - doi: 10.7490/f1000research.1114334.1
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Other
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Transcription factors and regulatory sites
    uri: http://edamontology.org/topic_0749
  - term: Sequencing
    uri: http://edamontology.org/topic_3168
  validated: 1
  version:
  - '1.0'
- accessibility: Open access
  additionDate: '2016-12-19T14:23:24Z'
  biotoolsCURIE: biotools:changename
  biotoolsID: changename
  collectionID:
  - galaxyPasteur
  - REPET
  confidence_flag: null
  cost: null
  credit:
  - email: galaxy@pasteur.fr
    fundrefid: null
    gridid: null
    name: Galaxy Support Team
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Change the chromosome name or gene name of a singla fasta, gff or sam
    file. For this tool, it can not treat mutiple-chromosome, gene files.
  documentation:
  - note: null
    type:
    - General
    url: https://galaxy.pasteur.fr/root?tool_id=toolshed.pasteur.fr%2Frepos%2Ffmareuil%2Furgi_tools%2FchangeName%2F1.0.0
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Data
        uri: http://edamontology.org/data_0006
      format:
      - term: GFF
        uri: http://edamontology.org/format_2305
    - data:
        term: Sequence trace
        uri: http://edamontology.org/data_0924
      format:
      - term: SAM
        uri: http://edamontology.org/format_2573
    note: null
    operation:
    - term: Sequence annotation
      uri: http://edamontology.org/operation_0361
    output:
    - data:
        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Data
        uri: http://edamontology.org/data_0006
      format:
      - term: GFF
        uri: http://edamontology.org/format_2305
    - data:
        term: Sequence trace
        uri: http://edamontology.org/data_0924
      format:
      - term: SAM
        uri: http://edamontology.org/format_2573
  homepage: https://urgi.versailles.inra.fr/Tools/REPET
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T13:57:21.291914Z'
  license: null
  link:
  - note: null
    type:
    - Galaxy service
    url: https://galaxy.pasteur.fr/tool_runner?tool_id=toolshed.pasteur.fr/repos/fmareuil/urgi_tools/changeName/1.0.0
  maturity: Mature
  name: changename
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: hmenager
  publication:
  - doi: 10.1093/nar/gkw343
    metadata:
      abstract: High-throughput data production technologies, particularly ‘next-generation’
        DNA sequencing, have ushered in widespread and disruptive changes to biomedical
        research. Making sense of the large datasets produced by these technologies
        requires sophisticated statistical and computational methods, as well as substantial
        computational power. This has led to an acute crisis in life sciences, as
        researchers without informatics training attempt to perform computation-dependent
        analyses. Since 2005, the Galaxy project has worked to address this problem
        by providing a framework that makes advanced computational tools usable by
        non experts. Galaxy seeks to make data-intensive research more accessible,
        transparent and reproducible by providing a Web-based environment in which
        users can perform computational analyses and have all of the details automatically
        tracked for later inspection, publication, or reuse. In this report we highlight
        recently added features enabling biomedical analyses on a large scale.
      authors:
      - name: Afgan E.
      - name: Baker D.
      - name: van den Beek M.
      - name: Blankenberg D.
      - name: Bouvier D.
      - name: Cech M.
      - name: Chilton J.
      - name: Clements D.
      - name: Coraor N.
      - name: Eberhard C.
      - name: Gruning B.
      - name: Guerler A.
      - name: Hillman-Jackson J.
      - name: Kuster G.V.
      - name: Rasche E.
      - name: Soranzo N.
      - name: Turaga N.
      - name: Taylor J.
      - name: Nekrutenko A.
      - name: Goecks J.
      citationCount: 1410
      date: '2016-07-08T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'The Galaxy platform for accessible, reproducible and collaborative biomedical
        analyses: 2016 update'
    note: null
    pmcid: PMC4987906
    pmid: '27137889'
    type:
    - Other
    version: null
  - doi: 10.7490/f1000research.1114334.1
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Other
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Sequencing
    uri: http://edamontology.org/topic_3168
  validated: 1
  version:
  - 1.0.0
- accessibility: Open access
  additionDate: '2016-12-19T14:29:37Z'
  biotoolsCURIE: biotools:restrictsequencelist
  biotoolsID: restrictsequencelist
  collectionID:
  - galaxyPasteur
  - REPET
  confidence_flag: null
  cost: null
  credit:
  - email: galaxy@pasteur.fr
    fundrefid: null
    gridid: null
    name: Galaxy Support Team
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Keep the elements of a list of sequences whose name is mentionned in
    a given file.
  documentation:
  - note: null
    type:
    - General
    url: https://galaxy.pasteur.fr/root?tool_id=toolshed.pasteur.fr%2Frepos%2Ffmareuil%2Furgi_tools%2FrestrictSequenceList%2F1.0.0
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
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        term: Sequence alignment
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    note: null
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      - name: Afgan E.
      - name: Baker D.
      - name: van den Beek M.
      - name: Blankenberg D.
      - name: Bouvier D.
      - name: Cech M.
      - name: Chilton J.
      - name: Clements D.
      - name: Coraor N.
      - name: Eberhard C.
      - name: Gruning B.
      - name: Guerler A.
      - name: Hillman-Jackson J.
      - name: Kuster G.V.
      - name: Rasche E.
      - name: Soranzo N.
      - name: Turaga N.
      - name: Taylor J.
      - name: Nekrutenko A.
      - name: Goecks J.
      citationCount: 1410
      date: '2016-07-08T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'The Galaxy platform for accessible, reproducible and collaborative biomedical
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    note: null
    pmcid: PMC4987906
    pmid: '27137889'
    type:
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    version: null
  - doi: 10.7490/f1000research.1114334.1
    metadata: null
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  version:
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  additionDate: '2016-12-19T14:27:00Z'
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    note: null
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      format:
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    metadata:
      abstract: High-throughput data production technologies, particularly ‘next-generation’
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        transparent and reproducible by providing a Web-based environment in which
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      - name: Baker D.
      - name: van den Beek M.
      - name: Blankenberg D.
      - name: Bouvier D.
      - name: Cech M.
      - name: Chilton J.
      - name: Clements D.
      - name: Coraor N.
      - name: Eberhard C.
      - name: Gruning B.
      - name: Guerler A.
      - name: Hillman-Jackson J.
      - name: Kuster G.V.
      - name: Rasche E.
      - name: Soranzo N.
      - name: Turaga N.
      - name: Taylor J.
      - name: Nekrutenko A.
      - name: Goecks J.
      citationCount: 1410
      date: '2016-07-08T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'The Galaxy platform for accessible, reproducible and collaborative biomedical
        analyses: 2016 update'
    note: null
    pmcid: PMC4987906
    pmid: '27137889'
    type:
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    version: null
  - doi: 10.7490/f1000research.1114334.1
    metadata: null
    note: null
    pmcid: null
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  toolType:
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  topic:
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  - term: Proteins
    uri: http://edamontology.org/topic_0078
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  description: This tool uses an iterative growth process and the use of sequence
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  - note: null
    type:
    - General
    url: https://galaxy.pasteur.fr/root?tool_id=toolshed.pasteur.fr%2Frepos%2Fmvalade%2Ffrogs%2FFROGS_clustering%2F2.3.0
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    - data:
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    note: null
    operation:
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    output:
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      format:
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    - data:
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    - data:
        term: Data
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  link:
  - note: null
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    url: https://galaxy.pasteur.fr/tool_runner?tool_id=toolshed.pasteur.fr/repos/mvalade/frogs/FROGS_clustering/2.3.0
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  name: frogs_clustering
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  otherID: []
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  - doi: 10.1093/nar/gkw343
    metadata:
      abstract: High-throughput data production technologies, particularly ‘next-generation’
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        computational power. This has led to an acute crisis in life sciences, as
        researchers without informatics training attempt to perform computation-dependent
        analyses. Since 2005, the Galaxy project has worked to address this problem
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        transparent and reproducible by providing a Web-based environment in which
        users can perform computational analyses and have all of the details automatically
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        recently added features enabling biomedical analyses on a large scale.
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      - name: Afgan E.
      - name: Baker D.
      - name: van den Beek M.
      - name: Blankenberg D.
      - name: Bouvier D.
      - name: Cech M.
      - name: Chilton J.
      - name: Clements D.
      - name: Coraor N.
      - name: Eberhard C.
      - name: Gruning B.
      - name: Guerler A.
      - name: Hillman-Jackson J.
      - name: Kuster G.V.
      - name: Rasche E.
      - name: Soranzo N.
      - name: Turaga N.
      - name: Taylor J.
      - name: Nekrutenko A.
      - name: Goecks J.
      citationCount: 1410
      date: '2016-07-08T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'The Galaxy platform for accessible, reproducible and collaborative biomedical
        analyses: 2016 update'
    note: null
    pmcid: PMC4987906
    pmid: '27137889'
    type:
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    version: null
  - doi: 10.7490/f1000research.1114334.1
    metadata: null
    note: null
    pmcid: null
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    type:
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    version: null
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  toolType:
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  - term: Microbial ecology
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  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  validated: 1
  version:
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  additionDate: '2016-12-19T14:22:03Z'
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  description: Keeps in each sample the same number of element by random sampling.
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    type:
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    input:
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    - data:
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    note: null
    operation:
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      uri: http://edamontology.org/operation_3435
    output:
    - data:
        term: Sequence alignment
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      format:
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        uri: http://edamontology.org/format_1929
    - data:
        term: Data
        uri: http://edamontology.org/data_0006
      format:
      - term: JSON
        uri: http://edamontology.org/format_3464
    - data:
        term: Report
        uri: http://edamontology.org/data_2048
      format:
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  homepage: http://frogs.toulouse.inra.fr/
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  lastUpdate: '2024-11-25T13:52:04.042588Z'
  license: null
  link:
  - note: null
    type:
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    url: https://galaxy.pasteur.fr/tool_runner?tool_id=toolshed.pasteur.fr/repos/mvalade/frogs/FROGS_normalisation/1.1.0
  maturity: Mature
  name: frogs_normalisation
  operatingSystem:
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  otherID: []
  owner: hmenager
  publication:
  - doi: 10.1093/nar/gkw343
    metadata:
      abstract: High-throughput data production technologies, particularly ‘next-generation’
        DNA sequencing, have ushered in widespread and disruptive changes to biomedical
        research. Making sense of the large datasets produced by these technologies
        requires sophisticated statistical and computational methods, as well as substantial
        computational power. This has led to an acute crisis in life sciences, as
        researchers without informatics training attempt to perform computation-dependent
        analyses. Since 2005, the Galaxy project has worked to address this problem
        by providing a framework that makes advanced computational tools usable by
        non experts. Galaxy seeks to make data-intensive research more accessible,
        transparent and reproducible by providing a Web-based environment in which
        users can perform computational analyses and have all of the details automatically
        tracked for later inspection, publication, or reuse. In this report we highlight
        recently added features enabling biomedical analyses on a large scale.
      authors:
      - name: Afgan E.
      - name: Baker D.
      - name: van den Beek M.
      - name: Blankenberg D.
      - name: Bouvier D.
      - name: Cech M.
      - name: Chilton J.
      - name: Clements D.
      - name: Coraor N.
      - name: Eberhard C.
      - name: Gruning B.
      - name: Guerler A.
      - name: Hillman-Jackson J.
      - name: Kuster G.V.
      - name: Rasche E.
      - name: Soranzo N.
      - name: Turaga N.
      - name: Taylor J.
      - name: Nekrutenko A.
      - name: Goecks J.
      citationCount: 1410
      date: '2016-07-08T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'The Galaxy platform for accessible, reproducible and collaborative biomedical
        analyses: 2016 update'
    note: null
    pmcid: PMC4987906
    pmid: '27137889'
    type:
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    version: null
  - doi: 10.7490/f1000research.1114334.1
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
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    version: null
  relation: []
  toolType:
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  topic:
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  - term: Sequencing
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  - term: Microbiology
    uri: http://edamontology.org/topic_3301
  validated: 1
  version:
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- accessibility: Open access
  additionDate: '2016-12-19T14:22:18Z'
  biotoolsCURIE: biotools:clc_unmapped_reads
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  credit:
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    fundrefid: null
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    name: Galaxy Support Team
    note: null
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    typeEntity: Person
    typeRole:
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    url: null
  description: Output the unmapped reads.
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  function:
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    input:
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        term: Data
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      format:
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        uri: http://edamontology.org/format_2333
    note: null
    operation:
    - term: DNA mapping
      uri: http://edamontology.org/operation_2520
    output:
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        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Data
        uri: http://edamontology.org/data_0006
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
  homepage: https://bio.tools/clcbio_genomics_workbench
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T13:51:32.678411Z'
  license: null
  link:
  - note: null
    type:
    - Galaxy service
    url: https://galaxy.pasteur.fr/tool_runner?tool_id=toolshed.pasteur.fr/repos/fmareuil/clc_assembly_4/clc_unmapped_reads/4.010.83648
  maturity: Mature
  name: clc_unmapped_reads
  operatingSystem:
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  - Windows
  - Mac
  otherID: []
  owner: hmenager
  publication:
  - doi: 10.1186/1471-2164-11-571
    metadata:
      abstract: 'Background: Roche 454 pyrosequencing has become a method of choice
        for generating transcriptome data from non-model organisms. Once the tens
        to hundreds of thousands of short (250-450 base) reads have been produced,
        it is important to correctly assemble these to estimate the sequence of all
        the transcripts. Most transcriptome assembly projects use only one program
        for assembling 454 pyrosequencing reads, but there is no evidence that the
        programs used to date are optimal. We have carried out a systematic comparison
        of five assemblers (CAP3, MIRA, Newbler, SeqMan and CLC) to establish best
        practices for transcriptome assemblies, using a new dataset from the parasitic
        nematode Litomosoides sigmodontis.Results: Although no single assembler performed
        best on all our criteria, Newbler 2.5 gave longer contigs, better alignments
        to some reference sequences, and was fast and easy to use. SeqMan assemblies
        performed best on the criterion of recapitulating known transcripts, and had
        more novel sequence than the other assemblers, but generated an excess of
        small, redundant contigs. The remaining assemblers all performed almost as
        well, with the exception of Newbler 2.3 (the version currently used by most
        assembly projects), which generated assemblies that had significantly lower
        total length. As different assemblers use different underlying algorithms
        to generate contigs, we also explored merging of assemblies and found that
        the merged datasets not only aligned better to reference sequences than individual
        assemblies, but were also more consistent in the number and size of contigs.Conclusions:
        Transcriptome assemblies are smaller than genome assemblies and thus should
        be more computationally tractable, but are often harder because individual
        contigs can have highly variable read coverage. Comparing single assemblers,
        Newbler 2.5 performed best on our trial data set, but other assemblers were
        closely comparable. Combining differently optimal assemblies from different
        programs however gave a more credible final product, and this strategy is
        recommended. © 2010 Kumar and Blaxter; licensee BioMed Central Ltd.'
      authors:
      - name: Kumar S.
      - name: Blaxter M.L.
      citationCount: 207
      date: '2010-10-16T00:00:00Z'
      journal: BMC Genomics
      title: Comparing de novo assemblers for 454 transcriptome data
    note: null
    pmcid: PMC3091720
    pmid: '20950480'
    type:
    - Review
    version: null
  - doi: 10.1093/nar/gkw343
    metadata:
      abstract: High-throughput data production technologies, particularly ‘next-generation’
        DNA sequencing, have ushered in widespread and disruptive changes to biomedical
        research. Making sense of the large datasets produced by these technologies
        requires sophisticated statistical and computational methods, as well as substantial
        computational power. This has led to an acute crisis in life sciences, as
        researchers without informatics training attempt to perform computation-dependent
        analyses. Since 2005, the Galaxy project has worked to address this problem
        by providing a framework that makes advanced computational tools usable by
        non experts. Galaxy seeks to make data-intensive research more accessible,
        transparent and reproducible by providing a Web-based environment in which
        users can perform computational analyses and have all of the details automatically
        tracked for later inspection, publication, or reuse. In this report we highlight
        recently added features enabling biomedical analyses on a large scale.
      authors:
      - name: Afgan E.
      - name: Baker D.
      - name: van den Beek M.
      - name: Blankenberg D.
      - name: Bouvier D.
      - name: Cech M.
      - name: Chilton J.
      - name: Clements D.
      - name: Coraor N.
      - name: Eberhard C.
      - name: Gruning B.
      - name: Guerler A.
      - name: Hillman-Jackson J.
      - name: Kuster G.V.
      - name: Rasche E.
      - name: Soranzo N.
      - name: Turaga N.
      - name: Taylor J.
      - name: Nekrutenko A.
      - name: Goecks J.
      citationCount: 1410
      date: '2016-07-08T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'The Galaxy platform for accessible, reproducible and collaborative biomedical
        analyses: 2016 update'
    note: null
    pmcid: PMC4987906
    pmid: '27137889'
    type:
    - Other
    version: null
  - doi: 10.7490/f1000research.1114334.1
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Other
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Sequencing
    uri: http://edamontology.org/topic_3168
  validated: 1
  version:
  - 4.010.83648
- accessibility: Open access
  additionDate: '2016-12-19T14:24:17Z'
  biotoolsCURIE: biotools:clc_find_variations
  biotoolsID: clc_find_variations
  collectionID:
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  - CLC Main Workbench
  confidence_flag: null
  cost: null
  credit:
  - email: galaxy@pasteur.fr
    fundrefid: null
    gridid: null
    name: Galaxy Support Team
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Find positions where the reads indicate a consistent difference from
    the reference sequences. Optionally, consensus sequences can be written to a fasta
    file.
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  - note: null
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    - User manual
    url: https://galaxy.pasteur.fr/root?tool_id=toolshed.pasteur.fr%2Frepos%2Ffmareuil%2Fclc_assembly_4%2Fclc_find_variations%2F4.4.2
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    - data:
        term: Data
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  homepage: https://bio.tools/clcbio_genomics_workbench
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  maturity: Mature
  name: clc_find_variations
  operatingSystem:
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  publication:
  - doi: 10.1186/1471-2164-11-571
    metadata:
      abstract: 'Background: Roche 454 pyrosequencing has become a method of choice
        for generating transcriptome data from non-model organisms. Once the tens
        to hundreds of thousands of short (250-450 base) reads have been produced,
        it is important to correctly assemble these to estimate the sequence of all
        the transcripts. Most transcriptome assembly projects use only one program
        for assembling 454 pyrosequencing reads, but there is no evidence that the
        programs used to date are optimal. We have carried out a systematic comparison
        of five assemblers (CAP3, MIRA, Newbler, SeqMan and CLC) to establish best
        practices for transcriptome assemblies, using a new dataset from the parasitic
        nematode Litomosoides sigmodontis.Results: Although no single assembler performed
        best on all our criteria, Newbler 2.5 gave longer contigs, better alignments
        to some reference sequences, and was fast and easy to use. SeqMan assemblies
        performed best on the criterion of recapitulating known transcripts, and had
        more novel sequence than the other assemblers, but generated an excess of
        small, redundant contigs. The remaining assemblers all performed almost as
        well, with the exception of Newbler 2.3 (the version currently used by most
        assembly projects), which generated assemblies that had significantly lower
        total length. As different assemblers use different underlying algorithms
        to generate contigs, we also explored merging of assemblies and found that
        the merged datasets not only aligned better to reference sequences than individual
        assemblies, but were also more consistent in the number and size of contigs.Conclusions:
        Transcriptome assemblies are smaller than genome assemblies and thus should
        be more computationally tractable, but are often harder because individual
        contigs can have highly variable read coverage. Comparing single assemblers,
        Newbler 2.5 performed best on our trial data set, but other assemblers were
        closely comparable. Combining differently optimal assemblies from different
        programs however gave a more credible final product, and this strategy is
        recommended. © 2010 Kumar and Blaxter; licensee BioMed Central Ltd.'
      authors:
      - name: Kumar S.
      - name: Blaxter M.L.
      citationCount: 207
      date: '2010-10-16T00:00:00Z'
      journal: BMC Genomics
      title: Comparing de novo assemblers for 454 transcriptome data
    note: null
    pmcid: PMC3091720
    pmid: '20950480'
    type:
    - Review
    version: null
  - doi: 10.1093/nar/gkw343
    metadata:
      abstract: High-throughput data production technologies, particularly ‘next-generation’
        DNA sequencing, have ushered in widespread and disruptive changes to biomedical
        research. Making sense of the large datasets produced by these technologies
        requires sophisticated statistical and computational methods, as well as substantial
        computational power. This has led to an acute crisis in life sciences, as
        researchers without informatics training attempt to perform computation-dependent
        analyses. Since 2005, the Galaxy project has worked to address this problem
        by providing a framework that makes advanced computational tools usable by
        non experts. Galaxy seeks to make data-intensive research more accessible,
        transparent and reproducible by providing a Web-based environment in which
        users can perform computational analyses and have all of the details automatically
        tracked for later inspection, publication, or reuse. In this report we highlight
        recently added features enabling biomedical analyses on a large scale.
      authors:
      - name: Afgan E.
      - name: Baker D.
      - name: van den Beek M.
      - name: Blankenberg D.
      - name: Bouvier D.
      - name: Cech M.
      - name: Chilton J.
      - name: Clements D.
      - name: Coraor N.
      - name: Eberhard C.
      - name: Gruning B.
      - name: Guerler A.
      - name: Hillman-Jackson J.
      - name: Kuster G.V.
      - name: Rasche E.
      - name: Soranzo N.
      - name: Turaga N.
      - name: Taylor J.
      - name: Nekrutenko A.
      - name: Goecks J.
      citationCount: 1410
      date: '2016-07-08T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'The Galaxy platform for accessible, reproducible and collaborative biomedical
        analyses: 2016 update'
    note: null
    pmcid: PMC4987906
    pmid: '27137889'
    type:
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    version: null
  - doi: 10.7490/f1000research.1114334.1
    metadata: null
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    version: null
  relation: []
  toolType:
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  topic:
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    uri: http://edamontology.org/topic_3168
  - term: Genetic variation
    uri: http://edamontology.org/topic_0199
  validated: 1
  version:
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- accessibility: Open access
  additionDate: '2016-12-19T14:22:35Z'
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  description: De novo assembly algorithm of CLC Assembly Cell for both short and
    long reads.
  documentation:
  - note: null
    type:
    - General
    url: https://galaxy.pasteur.fr/root?tool_id=toolshed.pasteur.fr%2Frepos%2Ffmareuil%2Fclc_assembly_4%2Fclc_assembler%2F4.4.2
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        uri: http://edamontology.org/format_1930
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Data
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      format:
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      - term: FASTA
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    - data:
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    - data:
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      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: null
    operation:
    - term: De-novo assembly
      uri: http://edamontology.org/operation_0524
    output:
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        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Data
        uri: http://edamontology.org/data_0006
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
    - data:
        term: Sequence assembly
        uri: http://edamontology.org/data_0925
      format:
      - term: AGP
        uri: http://edamontology.org/format_3693
    - data:
        term: Data
        uri: http://edamontology.org/data_0006
      format:
      - term: GFF
        uri: http://edamontology.org/format_2305
    - data:
        term: Data
        uri: http://edamontology.org/data_0006
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
  homepage: https://bio.tools/clcbio_genomics_workbench
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T13:51:15.191252Z'
  license: null
  link:
  - note: null
    type:
    - Galaxy service
    url: https://galaxy.pasteur.fr/tool_runner?tool_id=toolshed.pasteur.fr/repos/fmareuil/clc_assembly_4/clc_assembler/4.4.2
  maturity: Mature
  name: clc_assembler
  operatingSystem:
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  otherID: []
  owner: hmenager
  publication:
  - doi: 10.1002/ange.201507047
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Other
    version: null
  - doi: 10.1093/nar/gkw343
    metadata:
      abstract: High-throughput data production technologies, particularly ‘next-generation’
        DNA sequencing, have ushered in widespread and disruptive changes to biomedical
        research. Making sense of the large datasets produced by these technologies
        requires sophisticated statistical and computational methods, as well as substantial
        computational power. This has led to an acute crisis in life sciences, as
        researchers without informatics training attempt to perform computation-dependent
        analyses. Since 2005, the Galaxy project has worked to address this problem
        by providing a framework that makes advanced computational tools usable by
        non experts. Galaxy seeks to make data-intensive research more accessible,
        transparent and reproducible by providing a Web-based environment in which
        users can perform computational analyses and have all of the details automatically
        tracked for later inspection, publication, or reuse. In this report we highlight
        recently added features enabling biomedical analyses on a large scale.
      authors:
      - name: Afgan E.
      - name: Baker D.
      - name: van den Beek M.
      - name: Blankenberg D.
      - name: Bouvier D.
      - name: Cech M.
      - name: Chilton J.
      - name: Clements D.
      - name: Coraor N.
      - name: Eberhard C.
      - name: Gruning B.
      - name: Guerler A.
      - name: Hillman-Jackson J.
      - name: Kuster G.V.
      - name: Rasche E.
      - name: Soranzo N.
      - name: Turaga N.
      - name: Taylor J.
      - name: Nekrutenko A.
      - name: Goecks J.
      citationCount: 1410
      date: '2016-07-08T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'The Galaxy platform for accessible, reproducible and collaborative biomedical
        analyses: 2016 update'
    note: null
    pmcid: PMC4987906
    pmid: '27137889'
    type:
    - Other
    version: null
  - doi: 10.7490/f1000research.1114334.1
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
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    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Sequencing
    uri: http://edamontology.org/topic_3168
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  validated: 1
  version:
  - 4.4.2
- accessibility: Open access
  additionDate: '2016-12-19T14:27:49Z'
  biotoolsCURIE: biotools:crop
  biotoolsID: crop
  collectionID:
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  confidence_flag: null
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  credit:
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    fundrefid: null
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    name: Galaxy Support Team
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  description: A clustering tool which clusters 16S rRNA sequences into Operational
    Taxonomic Units (OTU).
  documentation: []
  download: []
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  function:
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    input:
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      format:
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        uri: http://edamontology.org/format_1929
    note: null
    operation:
    - term: Sequence clustering
      uri: http://edamontology.org/operation_0291
    output:
    - data:
        term: Data
        uri: http://edamontology.org/data_0006
      format:
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        uri: http://edamontology.org/format_2330
    - data:
        term: Data
        uri: http://edamontology.org/data_0006
      format:
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        uri: http://edamontology.org/format_2330
    - data:
        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format:
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        uri: http://edamontology.org/format_1929
  homepage: https://code.google.com/archive/p/crop-tingchenlab/
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T13:50:16.456270Z'
  license: null
  link:
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    type:
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    url: https://galaxy.pasteur.fr/tool_runner?tool_id=toolshed.pasteur.fr/repos/afelten/microbiome_analyses/CROP/1.33
  maturity: Mature
  name: crop
  operatingSystem:
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  - Windows
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  otherID: []
  owner: hmenager
  publication:
  - doi: 10.1093/bioinformatics/btq725
    metadata:
      abstract: 'Motivation: With the advancements of next-generation sequencing technology,
        it is now possible to study samples directly obtained from the environment.
        Particularly, 16S rRNA gene sequences have been frequently used to profile
        the diversity of organisms in a sample. However, such studies are still taxed
        to determine both the number of operational taxonomic units (OTUs) and their
        relative abundance in a sample. Results: To address these challenges, we propose
        an unsupervised Bayesian clustering method termed Clustering 16S rRNA for
        OTU Prediction (CROP). CROP can find clusters based on the natural organization
        of data without setting a hard cut-off threshold (3%/5%) as required by hierarchical
        clustering methods. By applying our method to several datasets, we demonstrate
        that CROP is robust against sequencing errors and that it produces more accurate
        results than conventional hierarchical clustering methods. © The Author(s)
        2011. Published by Oxford University Press.'
      authors:
      - name: Hao X.
      - name: Jiang R.
      - name: Chen T.
      citationCount: 208
      date: '2011-03-01T00:00:00Z'
      journal: Bioinformatics
      title: 'Clustering 16S rRNA for OTU prediction: A method of unsupervised Bayesian
        clustering'
    note: null
    pmcid: PMC3042185
    pmid: '21233169'
    type:
    - Primary
    version: null
  - doi: 10.1093/nar/gkw343
    metadata:
      abstract: High-throughput data production technologies, particularly ‘next-generation’
        DNA sequencing, have ushered in widespread and disruptive changes to biomedical
        research. Making sense of the large datasets produced by these technologies
        requires sophisticated statistical and computational methods, as well as substantial
        computational power. This has led to an acute crisis in life sciences, as
        researchers without informatics training attempt to perform computation-dependent
        analyses. Since 2005, the Galaxy project has worked to address this problem
        by providing a framework that makes advanced computational tools usable by
        non experts. Galaxy seeks to make data-intensive research more accessible,
        transparent and reproducible by providing a Web-based environment in which
        users can perform computational analyses and have all of the details automatically
        tracked for later inspection, publication, or reuse. In this report we highlight
        recently added features enabling biomedical analyses on a large scale.
      authors:
      - name: Afgan E.
      - name: Baker D.
      - name: van den Beek M.
      - name: Blankenberg D.
      - name: Bouvier D.
      - name: Cech M.
      - name: Chilton J.
      - name: Clements D.
      - name: Coraor N.
      - name: Eberhard C.
      - name: Gruning B.
      - name: Guerler A.
      - name: Hillman-Jackson J.
      - name: Kuster G.V.
      - name: Rasche E.
      - name: Soranzo N.
      - name: Turaga N.
      - name: Taylor J.
      - name: Nekrutenko A.
      - name: Goecks J.
      citationCount: 1410
      date: '2016-07-08T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'The Galaxy platform for accessible, reproducible and collaborative biomedical
        analyses: 2016 update'
    note: null
    pmcid: PMC4987906
    pmid: '27137889'
    type:
    - Other
    version: null
  - doi: 10.7490/f1000research.1114334.1
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Other
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: RNA-Seq
    uri: http://edamontology.org/topic_3170
  - term: Sequencing
    uri: http://edamontology.org/topic_3168
  - term: Taxonomy
    uri: http://edamontology.org/topic_0637
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  validated: 1
  version:
  - '1.33'
- accessibility: Open access
  additionDate: '2016-12-19T14:26:05Z'
  biotoolsCURIE: biotools:noisy
  biotoolsID: noisy
  collectionID:
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  confidence_flag: null
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  credit:
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    fundrefid: null
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    name: Galaxy Support Team
    note: null
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    typeEntity: Person
    typeRole:
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    url: null
  description: Cleaning aligned sequences.
  documentation:
  - note: null
    type:
    - User manual
    url: http://www.bioinf.uni-leipzig.de/Software/noisy/noisy.1.html#lbAD
  download: []
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  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Sequence alignment
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      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Data
        uri: http://edamontology.org/data_0006
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
    note: null
    operation:
    - term: Sequence alignment editing
      uri: http://edamontology.org/operation_3081
    output:
    - data:
        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Data
        uri: http://edamontology.org/data_0006
      format:
      - term: EPS
        uri: http://edamontology.org/format_3466
    - data:
        term: Data
        uri: http://edamontology.org/data_0006
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
  homepage: http://www.bioinf.uni-leipzig.de/Software/noisy/
  homepage_status: 0
  language:
  - C++
  lastUpdate: '2024-11-25T13:48:48.576677Z'
  license: null
  link:
  - note: null
    type:
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    url: https://galaxy.pasteur.fr/tool_runner?tool_id=toolshed.pasteur.fr/repos/fmareuil/noisy/noisy/1.5.12.1
  maturity: Mature
  name: noisy
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: hmenager
  publication:
  - doi: 10.1186/1748-7188-3-7
    metadata:
      abstract: 'Motivation: Sequence-based methods for phylogenetic reconstruction
        from (nucleic acid) sequence data are notoriously plagued by two effects:
        homoplasies and alignment errors. Large evolutionary distances imply a large
        number of homoplastic sites. As most protein-coding genes show dramatic variations
        in substitution rates that are not uncorrelated across the sequence, this
        often leads to a patchwork pattern of (i) phylogenetically informative and
        (ii) effectively randomized regions. In highly variable regions, furthermore,
        alignment errors accumulate resulting in sometimes misleading signals in phylogenetic
        reconstruction. Results: We present here a method that, based on assessing
        the distribution of character states along a cyclic ordering of the taxa,
        allows the identification of phylogenetically uninformative homoplastic sites
        in a multiple sequence alignment. Removal of these sites appears to improve
        the performance of phylogenetic reconstruction algorithms as measured by various
        indices of "tree quality". In particular, we obtain more stable trees due
        to the exclusion of phylogenetically incompatible sites that most likely represent
        strongly randomized characters. Software: The computer program noisy implements
        this approach. It can be employed to improving phylogenetic reconstruction
        capability with quite a considerable success rate whenever (1) the average
        bootstrap support obtained from the original alignment is low, and (2) there
        are sufficiently many taxa in the data set - at least, say, 12 to 15 taxa.
        The software can be obtained under the GNU Public License from http://www.bioinf.uni-leipzig.de/Software/noisy/.
        © 2008 Dress et al; licensee BioMed Central Ltd.'
      authors:
      - name: Dress A.W.M.
      - name: Flamm C.
      - name: Fritzsch G.
      - name: Grunewald S.
      - name: Kruspe M.
      - name: Prohaska S.J.
      - name: Stadler P.F.
      citationCount: 116
      date: '2008-06-24T00:00:00Z'
      journal: Algorithms for Molecular Biology
      title: 'Noisy: Identification of problematic columns in multiple sequence alignments'
    note: null
    pmcid: PMC2464588
    pmid: '18577231'
    type:
    - Primary
    version: null
  - doi: 10.1093/nar/gkw343
    metadata:
      abstract: High-throughput data production technologies, particularly ‘next-generation’
        DNA sequencing, have ushered in widespread and disruptive changes to biomedical
        research. Making sense of the large datasets produced by these technologies
        requires sophisticated statistical and computational methods, as well as substantial
        computational power. This has led to an acute crisis in life sciences, as
        researchers without informatics training attempt to perform computation-dependent
        analyses. Since 2005, the Galaxy project has worked to address this problem
        by providing a framework that makes advanced computational tools usable by
        non experts. Galaxy seeks to make data-intensive research more accessible,
        transparent and reproducible by providing a Web-based environment in which
        users can perform computational analyses and have all of the details automatically
        tracked for later inspection, publication, or reuse. In this report we highlight
        recently added features enabling biomedical analyses on a large scale.
      authors:
      - name: Afgan E.
      - name: Baker D.
      - name: van den Beek M.
      - name: Blankenberg D.
      - name: Bouvier D.
      - name: Cech M.
      - name: Chilton J.
      - name: Clements D.
      - name: Coraor N.
      - name: Eberhard C.
      - name: Gruning B.
      - name: Guerler A.
      - name: Hillman-Jackson J.
      - name: Kuster G.V.
      - name: Rasche E.
      - name: Soranzo N.
      - name: Turaga N.
      - name: Taylor J.
      - name: Nekrutenko A.
      - name: Goecks J.
      citationCount: 1410
      date: '2016-07-08T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'The Galaxy platform for accessible, reproducible and collaborative biomedical
        analyses: 2016 update'
    note: null
    pmcid: PMC4987906
    pmid: '27137889'
    type:
    - Other
    version: null
  - doi: 10.7490/f1000research.1114334.1
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Other
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Sequencing
    uri: http://edamontology.org/topic_3168
  validated: 1
  version:
  - 1.5.12.1
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  additionDate: '2016-12-19T14:28:29Z'
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next: ?page=2
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