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  confidence_flag: null
  cost: Free of charge
  credit: []
  description: PathBench-MIL is a comprehensive, flexible benchmarking/AutoML framework
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    be deprecated and replaced by PathForge.
  documentation: []
  download: []
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      format:
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    - data:
        term: Image
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      format:
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        uri: http://edamontology.org/format_3591
    note: null
    operation:
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    - term: Visualisation
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    - term: Regression analysis
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    - term: Classification
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    - data:
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      format:
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        uri: http://edamontology.org/format_2331
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  homepage_status: 0
  language:
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  - Python
  lastUpdate: '2026-08-18T09:47:11.729879Z'
  license: GPL-3.0
  link: []
  maturity: Legacy
  name: PathBench-MIL
  operatingSystem:
  - Linux
  otherID: []
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    metadata: null
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation:
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    type: hasNewVersion
  toolType: []
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    uri: http://edamontology.org/topic_0634
  - term: Machine learning
    uri: http://edamontology.org/topic_3474
  validated: 0
  version: []
- accessibility: Open access
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  biotoolsCURIE: biotools:bakta
  biotoolsID: bakta
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit:
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    fundrefid: null
    gridid: null
    name: Oliver Schwengers
    note: null
    orcidid: https://orcid.org/0000-0003-4216-2721
    rorid: null
    typeEntity: Person
    typeRole:
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    - Developer
    - Maintainer
    url: https://github.com/oschwengers
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    note: null
    orcidid: null
    rorid: null
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    typeRole:
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  description: Rapid & standardized annotation of bacterial genomes, MAGs & plasmids
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  - note: null
    type:
    - Contributions policy
    url: https://github.com/oschwengers/bakta/blob/main/CONTRIBUTION.md
  - note: null
    type:
    - Code of conduct
    url: https://github.com/oschwengers/bakta/blob/main/CODE_OF_CONDUCT.md
  - note: null
    type:
    - User manual
    url: https://bakta.readthedocs.io/
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  - note: Mandatory annotation database
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    version: v6.0
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      format:
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    - data:
        term: Sequence features metadata
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      format:
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        uri: http://edamontology.org/format_3475
    - data:
        term: Sequence coordinates
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      format:
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        uri: http://edamontology.org/format_1975
    - data:
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      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Hidden Markov model
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      format:
      - term: HMMER3
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    note: null
    operation:
    - term: Genome annotation
      uri: http://edamontology.org/operation_0362
    output:
    - data:
        term: Feature table
        uri: http://edamontology.org/data_1270
      format:
      - term: GenBank format
        uri: http://edamontology.org/format_1936
      - term: JSON
        uri: http://edamontology.org/format_3464
      - term: EMBL format
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      - term: GFF3
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      - term: TSV
        uri: http://edamontology.org/format_3475
    - data:
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      format:
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        uri: http://edamontology.org/format_1929
    - data:
        term: Nucleic acid sequence record
        uri: http://edamontology.org/data_2887
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Plot
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      format:
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        uri: http://edamontology.org/format_3603
      - term: SVG
        uri: http://edamontology.org/format_3604
    - data:
        term: Score
        uri: http://edamontology.org/data_1772
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
  homepage: https://github.com/oschwengers/bakta
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2026-08-07T07:24:30.787190Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/oschwengers/bakta
  - note: null
    type:
    - Issue tracker
    url: https://github.com/oschwengers/bakta/issues
  - note: null
    type:
    - Other
    url: https://bioconda.github.io/recipes/bakta/README.html
  - note: null
    type:
    - Service
    url: https://bakta.computational.bio
  maturity: Mature
  name: Bakta
  operatingSystem:
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  - Mac
  otherID: []
  owner: oschwengers
  publication:
  - doi: 10.1099/mgen.0.000685
    metadata: null
    note: null
    pmcid: PMC8743544
    pmid: '34739369'
    type:
    - Primary
    version: '1.1'
  - doi: 10.1093/nar/gkaf335
    metadata: null
    note: null
    pmcid: PMC12230652
    pmid: '40271661'
    type:
    - Primary
    version: null
  relation:
  - biotoolsID: diamond
    type: uses
  - biotoolsID: hmmer3
    type: uses
  - biotoolsID: infernal
    type: uses
  - biotoolsID: trnascan-se
    type: uses
  - biotoolsID: blast
    type: uses
  - biotoolsID: aragorn
    type: uses
  - biotoolsID: pilercr
    type: uses
  toolType:
  - Command-line tool
  - Web application
  topic:
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  validated: 0
  version:
  - v1.12.1
- accessibility: Open access
  additionDate: '2026-08-04T04:51:20.841163Z'
  biotoolsCURIE: biotools:bioszen
  biotoolsID: bioszen
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: bioszenf@gmail.com
    fundrefid: null
    gridid: null
    name: Benjamín Szenfeld
    note: null
    orcidid: https://orcid.org/0009-0003-4702-4149
    rorid: null
    typeEntity: Person
    typeRole:
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    - Maintainer
    - Primary contact
    url: null
  description: "BIOSZEN is an open-source R package and modular Shiny application\
    \ for reproducible analysis and visualization of experimental biological data\
    \ from Excel or CSV files. It supports statistical testing, control-based normalization,\
    \ replicate-aware quality control, and customizable scientific plots. \nIts microbial\
    \ growth-curve module analyzes optical-density time series and automatically extracts\
    \ quantitative growth parameters, including maximum specific growth rate (µMax),\
    \ doubling time, lag time, maximum optical density (ODmax), time to maximum growth,\
    \ area under the curve (AUC), and initial optical density (OD0). \nResults can\
    \ be exported as processed datasets, statistical summaries, analysis metadata,\
    \ scientific graphics, and editable PowerPoint figures."
  documentation:
  - note: null
    type:
    - General
    - User manual
    - Quick start guide
    url: https://github.com/bioszen/BIOSZEN#readme
  - note: Complete BIOSZEN user manual in English.
    type:
    - User manual
    url: https://github.com/bioszen/BIOSZEN/blob/main/inst/app/www/MANUAL_EN.md
  - note: null
    type:
    - Citation instructions
    url: https://github.com/bioszen/BIOSZEN#citation
  download:
  - note: Archived release files and permanent software record.
    type: Downloads page
    url: https://zenodo.org/records/18217210
    version: 2.1.1
  - note: Installable R package for BIOSZEN 2.1.1, including access to the Shiny application.
    type: Software package
    url: https://bioszen.r-universe.dev/BIOSZEN
    version: 2.1.1
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: Statistical analysis, control-based normalization, replicate-aware quality
      control, and customizable visualization of experimental biological data from
      Excel or CSV files.
    operation:
    - term: Statistical calculation
      uri: http://edamontology.org/operation_2238
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    output: []
  - cmd: null
    input: []
    note: Analysis and visualization of microbial optical-density time series, including
      extraction of uMax, max_percap_time, doubling time, lag time, ODmax, max_time,
      AUC, OD0, and related growth parameters.
    operation:
    - term: Statistical calculation
      uri: http://edamontology.org/operation_2238
    - term: Data analysis
      uri: http://edamontology.org/operation_2945
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    output: []
  homepage: https://github.com/bioszen/BIOSZEN
  homepage_status: 0
  language:
  - R
  lastUpdate: '2026-08-06T16:57:58.462807Z'
  license: GPL-3.0
  link:
  - note: Source code, example files, documentation, and development history.
    type:
    - Repository
    url: https://github.com/bioszen/BIOSZEN
  - note: Bug reports, installation problems, and feature suggestions.
    type:
    - Issue tracker
    url: https://github.com/bioszen/BIOSZEN/issues
  - note: Limited online demonstration of the BIOSZEN Shiny application.
    type:
    - Service
    url: https://bioszen-test.share.connect.posit.cloud
  maturity: null
  name: BIOSZEN
  operatingSystem:
  - Windows
  - Mac
  otherID: []
  owner: benjamin7
  publication:
  - doi: 10.5281/zenodo.18217210
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: all versions
  - doi: 10.5281/zenodo.18217522
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: 1.0.0
  relation: []
  toolType:
  - Desktop application
  - Web application
  topic:
  - term: Data visualisation
    uri: http://edamontology.org/topic_0092
  - term: Statistics and probability
    uri: http://edamontology.org/topic_2269
  - term: Microbiology
    uri: http://edamontology.org/topic_3301
  validated: 0
  version:
  - 2.1.1
- accessibility: null
  additionDate: '2019-11-14T19:50:03Z'
  biotoolsCURIE: biotools:RNATracker
  biotoolsID: RNATracker
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: blanchem@cs.mcgill.ca
    fundrefid: null
    gridid: null
    name: Mathieu Blanchette
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: Prediction of mRNA subcellular localization using deep recurrent neural
    networks | RNATracker is a deep learning approach to learn mRNA subcellular localization
    patterns and to infer its outcome. It operates on the cDNA of the longest isoformic
    protein-coding transcript of a gene with or without its corresponding secondary
    structure annnotations. The learning targets are fractions/percentage of the transcripts
    being localized to a fixed set of subcellular compartments of interest
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Subcellular localisation prediction
      uri: http://edamontology.org/operation_2489
    - term: trans-regulatory element prediction
      uri: http://edamontology.org/operation_0443
    output: []
  homepage: https://www.github.com/HarveyYan/RNATracker
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2026-08-02T05:55:43.612294Z'
  license: GPL-3.0
  link: []
  maturity: null
  name: RNATracker
  operatingSystem: []
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1093/BIOINFORMATICS/BTZ337
    metadata: null
    note: null
    pmcid: PMC6612824
    pmid: '31510698'
    type: []
    version: null
  relation: []
  toolType: []
  topic:
  - term: Gene transcripts
    uri: http://edamontology.org/topic_3512
  - term: Machine learning
    uri: http://edamontology.org/topic_3474
  - term: Gene expression
    uri: http://edamontology.org/topic_0203
  validated: 1
  version: []
- accessibility: null
  additionDate: '2021-01-18T08:45:59Z'
  biotoolsCURIE: biotools:csp-analyzer
  biotoolsID: csp-analyzer
  collectionID: []
  confidence_flag: tool
  cost: null
  credit:
  - email: grzegorz.popowicz@helmholtz-muenchen.de
    fundrefid: null
    gridid: null
    name: G.M. Popowicz
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: 'A novel Machine Learning-based application for automated analysis
    of two-dimensional NMR spectra in NMR fragment-based screening.


    A fast and efficient multi-spectrum anlayzer for 2-D NMR Fragment Screening based
    on SMOTE-ENN machine-learning discriminator. - rubbs14/CSP-Analyzer.'
  documentation: []
  download: []
  editPermission:
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  elixirNode: []
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  function:
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    input: []
    note: null
    operation:
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      uri: http://edamontology.org/operation_3215
    - term: Essential dynamics
      uri: http://edamontology.org/operation_3891
    - term: Spectrum calculation
      uri: http://edamontology.org/operation_3860
    output: []
  homepage: https://github.com/rubbs14/CSP-Analyzer/releases/tag/v1.0
  homepage_status: 0
  language:
  - C#
  - Python
  lastUpdate: '2026-07-27T14:35:54.373975Z'
  license: GPL-3.0
  link: []
  maturity: null
  name: CSP-Analyzer
  operatingSystem: []
  otherID: []
  owner: roberto
  publication:
  - doi: 10.1016/J.CSBJ.2020.02.015
    metadata:
      abstract: © 2020 The AuthorsNMR-based screening, especially fragment-based drug
        discovery is a valuable approach in early-stage drug discovery. Monitoring
        fragment-binding in protein-detected 2D NMR experiments requires analysis
        of hundreds of spectra to detect chemical shift perturbations (CSPs) in the
        presence of ligands screened. Computational tools are available that simplify
        the tracking of CSPs in 2D NMR spectra. However, to the best of our knowledge,
        an efficient automated tool for the assessment and binning of multiple spectra
        for ligand binding has not yet been described. We present a novel and fast
        approach for analysis of multiple 2D HSQC spectra based on machine-learning-driven
        statistical discrimination. The CSP Analyzer features a C# frontend interfaced
        to a Python ML classifier. The software allows rapid evaluation of 2D screening
        data from large number of spectra, reducing user-introduced bias in the evaluation.
        The CSP Analyzer software package is available on GitHub https://github.com/rubbs14/CSP-Analyzer/releases/tag/v1.0
        under the GPL license 3.0 and is free to use for academic and commercial uses.
      authors:
      - name: Fino R.
      - name: Byrne R.
      - name: Softley C.A.
      - name: Sattler M.
      - name: Schneider G.
      - name: Popowicz G.M.
      citationCount: 2
      date: '2020-01-01T00:00:00Z'
      journal: Computational and Structural Biotechnology Journal
      title: 'Introducing the CSP Analyzer: A novel Machine Learning-based application
        for automated analysis of two-dimensional NMR spectra in NMR fragment-based
        screening'
    note: null
    pmcid: PMC7096735
    pmid: '32257044'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: NMR
    uri: http://edamontology.org/topic_0593
  - term: Machine learning
    uri: http://edamontology.org/topic_3474
  - term: Drug discovery
    uri: http://edamontology.org/topic_3336
  validated: 0
  version: []
- accessibility: null
  additionDate: '2015-01-22T11:13:24Z'
  biotoolsCURIE: biotools:clustvis
  biotoolsID: clustvis
  collectionID:
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  confidence_flag: null
  cost: Free of charge
  credit:
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    fundrefid: null
    gridid: null
    name: ELIXIR-EE
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: tauno.metsalu@ut.ee
    fundrefid: null
    gridid: null
    name: Tauno Metsalu
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: biit.support@ut.ee
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Web tool which allows users to upload their own data and easily create
    Principal Component Analysis (PCA) plots and heatmaps. Data can be uploaded as
    a file or by copy-pasteing it to the text box.
  documentation:
  - note: null
    type:
    - General
    url: https://biit.cs.ut.ee/clustvis/
  download:
  - note: Docker image
    type: Container file
    url: https://hub.docker.com/r/taunometsalu/clustvis/
    version: null
  editPermission:
    authors:
    - may.kay
    - sssjh
    type: group
  elixirCommunity: []
  elixirNode:
  - Estonia
  elixirPlatform:
  - Tools
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Processed microarray data
        uri: http://edamontology.org/data_3111
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
      - term: Matrix format
        uri: http://edamontology.org/format_3033
    - data:
        term: Sample annotation
        uri: http://edamontology.org/data_3113
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
      - term: Matrix format
        uri: http://edamontology.org/format_3033
    - data:
        term: Gene expression profile
        uri: http://edamontology.org/data_0928
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
      - term: Matrix format
        uri: http://edamontology.org/format_3033
    note: null
    operation:
    - term: Gene expression clustering
      uri: http://edamontology.org/operation_0313
    - term: Treemap visualisation
      uri: http://edamontology.org/operation_2942
    - term: Statistical calculation
      uri: http://edamontology.org/operation_2238
    - term: Principal component plotting
      uri: http://edamontology.org/operation_2939
    - term: Heat map generation
      uri: http://edamontology.org/operation_0531
    output:
    - data:
        term: Heat map
        uri: http://edamontology.org/data_1636
      format:
      - term: EPS
        uri: http://edamontology.org/format_3466
      - term: SVG
        uri: http://edamontology.org/format_3604
      - term: PDF
        uri: http://edamontology.org/format_3508
    - data:
        term: Image
        uri: http://edamontology.org/data_2968
      format:
      - term: EPS
        uri: http://edamontology.org/format_3466
      - term: SVG
        uri: http://edamontology.org/format_3604
      - term: PDF
        uri: http://edamontology.org/format_3508
  homepage: http://biit.cs.ut.ee/clustvis
  homepage_status: 0
  language:
  - R
  lastUpdate: '2026-07-21T21:16:04.483218Z'
  license: GPL-3.0
  link:
  - note: A code repository in github.
    type:
    - Repository
    url: https://github.com/taunometsalu/ClustVis
  maturity: null
  name: ClustVis
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID:
  - type: rrid
    value: RRID:SCR_017133
    version: null
  owner: user.1781877465
  publication:
  - doi: 10.1093/nar/gkv468
    metadata:
      abstract: 'The Principal Component Analysis (PCA) is a widely used method of
        reducing the dimensionality of highdimensional data, often followed by visualizing
        two of the components on the scatterplot. Although widely used, the method
        is lacking an easy-to-use web interface that scientists with little programming
        skills could use to make plots of their own data. The same applies to creating
        heatmaps: it is possible to add conditional formatting for Excel cells to
        show colored heatmaps, but for more advanced features such as clustering and
        experimental annotations, more sophisticated analysis tools have to be used.
        We present a web tool called ClustVis that aims to have an intuitive user
        interface. Users can upload data from a simple delimited text file that can
        be created in a spreadsheet program. It is possible to modify data processing
        methods and the final appearance of the PCA and heatmap plots by using drop-down
        menus, text boxes, sliders etc. Appropriate defaults are given to reduce the
        time needed by the user to specify input parameters. As an output, users can
        download PCA plot and heatmap in one of the preferred file formats. This web
        server is freely available at http://biit.cs.ut.ee/clustvis/.'
      authors:
      - name: Metsalu T.
      - name: Vilo J.
      citationCount: 2504
      date: '2015-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'ClustVis: A web tool for visualizing clustering of multivariate data
        using Principal Component Analysis and heatmap'
    note: null
    pmcid: PMC4489295
    pmid: '25969447'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Data visualisation
    uri: http://edamontology.org/topic_0092
  - term: Statistics and probability
    uri: http://edamontology.org/topic_2269
  validated: 1
  version:
  - '1'
- accessibility: null
  additionDate: '2017-08-20T15:58:06Z'
  biotoolsCURIE: biotools:moods
  biotoolsID: moods
  collectionID:
  - Animal and Crop Genomics
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  credit:
  - email: janne.h.korhonen@aalto.fi
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: A suite of algorithms for matching position weight matrices (PWM) against
    DNA sequences. It features advanced matrix matching algorithms implemented in
    C++ that can be used to scan hundreds of matrices against chromosome-sized sequences
    in few seconds. MOODS can also process high-order PWMs with dependencies between
    adjacent positions and sequence variants such as SNPs, insertions and deletions.
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/jhkorhonen/MOODS/wiki/Getting-started
  download: []
  editPermission:
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  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Sequence motif recognition
      uri: http://edamontology.org/operation_0239
    output: []
  homepage: https://www.cs.helsinki.fi/group/pssmfind/
  homepage_status: 0
  language:
  - C++
  - Python
  lastUpdate: '2026-07-21T21:15:59.464608Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/jhkorhonen/MOODS
  - note: null
    type:
    - Issue tracker
    url: https://github.com/jhkorhonen/MOODS/issues
  maturity: null
  name: MOODS
  operatingSystem:
  - Linux
  otherID: []
  owner: Bamboo
  publication:
  - doi: 10.1109/tcbb.2009.35
    metadata:
      abstract: Position weight matrices are an important method for modeling signals
        or motifs in biological sequences, both in DNA and protein contexts. In this
        paper, we present fast algorithms for the problem of finding significant matches
        of such matrices. Our algorithms are of the online type, and they generalize
        classical multipattern matching, filtering, and superalphabet techniques of
        combinatorial string matching to the problem of weight matrix matching. Several
        variants of the algorithms are developed, including multiple matrix extensions
        that perform the search for several matrices in one scan through the sequence
        database. Experimental performance evaluation is provided to compare the new
        techniques against each other as well as against some other online and index-based
        algorithms proposed in the literature. Compared to the brute-force O(mn) approach,
        our solutions can be faster by a factor that is proportional to the matrix
        length m. Our multiple-matrix filtration algorithm had the best performance
        in the experiments. On a current PC, this algorithm finds significant matches
        (p = 0.0001) of the 123 JASPAR matrices in the human genome in about 18 minutes.
        © 2011 IEEE.
      authors:
      - name: Pizzi C.
      - name: Rastas P.
      - name: Ukkonen E.
      citationCount: 24
      date: '2011-01-01T00:00:00Z'
      journal: IEEE/ACM Transactions on Computational Biology and Bioinformatics
      title: Finding significant matches of position weight matrices in linear time
    note: null
    pmcid: null
    pmid: '21071798'
    type:
    - Primary
    version: null
  - doi: 10.1093/bioinformatics/btw683
    metadata:
      abstract: 'Motivation: While the position weight matrix (PWM) is the most popular
        model for sequence motifs, there is growing evidence of the usefulness of
        more advanced models such as first-order Markov representations, and such
        models are also becoming available in well-known motif databases. There has
        been lots of research of how to learn these models from training data but
        the problem of predicting putative sites of the learned motifs by matching
        the model against new sequences has been given less attention. Moreover, motif
        site analysis is often concerned about how different variants in the sequence
        affect the sites. So far, though, the corresponding efficient software tools
        for motif matching have been lacking. Results: We develop fast motif matching
        algorithms for the aforementioned tasks. First, we formalize a framework based
        on high-order position weight matrices for generic representation of motif
        models with dinucleotide or general q-mer dependencies, and adapt fast PWM
        matching algorithms to the high-order PWM framework. Second, we show how to
        incorporate different types of sequence variants, such as SNPs and indels,
        and their combined effects into efficient PWM matching workflows. Benchmark
        results show that our algorithms perform well in practice on genome-sized
        sequence sets and are for multiple motif search much faster than the basic
        sliding window algorithm.'
      authors:
      - name: Korhonen J.H.
      - name: Palin K.
      - name: Taipale J.
      - name: Ukkonen E.
      citationCount: 23
      date: '2017-02-15T00:00:00Z'
      journal: Bioinformatics
      title: 'Fast motif matching revisited: High-order PWMs, SNPs and indels'
    note: null
    pmcid: null
    pmid: '28011774'
    type:
    - Primary
    version: null
  - doi: 10.1093/bioinformatics/btp554
    metadata:
      abstract: 'Summary: MOODS (MOtif Occurrence Detection Suite) is a software package
        for matching position weight matrices against DNA sequences. MOODS implements
        state-of-the-art online matching algorithms, achieving considerably faster
        scanning speed than with a simple brute-force search. MOODS is written in
        C++, with bindings for the popular BioPerl and Biopython toolkits. It can
        easily be adapted for different purposes and integrated into existing workflows.
        It can also be used as a C++ library. © The Author(s) 2009. Published by Oxford
        University Press.'
      authors:
      - name: Korhonen J.
      - name: Martinmaki P.
      - name: Pizzi C.
      - name: Rastas P.
      - name: Ukkonen E.
      citationCount: 116
      date: '2009-09-22T00:00:00Z'
      journal: Bioinformatics
      title: 'MOODS: Fast search for position weight matrix matches in DNA sequences'
    note: null
    pmcid: PMC2778336
    pmid: '19773334'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  - Script
  topic:
  - term: Mapping
    uri: http://edamontology.org/topic_0102
  - term: Sequence composition, complexity and repeats
    uri: http://edamontology.org/topic_0157
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2022-07-26T10:11:09.660345Z'
  biotoolsCURIE: biotools:pangolin
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  credit:
  - email: yangili1@uchicago.edu
    fundrefid: null
    gridid: null
    name: Yang I Li
    note: null
    orcidid: https://orcid.org/0000-0002-0736-251X
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Tony Zeng
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  description: Pangolin is a deep-learning based method for predicting splice site
    strengths (for details, see Zeng and Li, Genome Biology 2022). It is available
    as a command-line tool that can be run on a VCF or CSV file containing variants
    of interest; Pangolin will predict changes in splice site strength due to each
    variant, and return a file of the same format. Pangolin's models can also be used
    with custom sequences.
  documentation: []
  download: []
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  function:
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    note: null
    operation:
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    - term: Sequence merging
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    - term: Alternative splicing prediction
      uri: http://edamontology.org/operation_0264
    - term: Genotyping
      uri: http://edamontology.org/operation_3196
    - term: Variant classification
      uri: http://edamontology.org/operation_3225
    output: []
  homepage: https://github.com/tkzeng/Pangolin
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2026-07-21T21:15:53.848510Z'
  license: GPL-3.0
  link: []
  maturity: null
  name: Pangolin
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  - Linux
  - Windows
  otherID: []
  owner: Jennifer
  publication:
  - doi: 10.1186/s13059-022-02664-4
    metadata:
      abstract: Recent progress in deep learning has greatly improved the prediction
        of RNA splicing from DNA sequence. Here, we present Pangolin, a deep learning
        model to predict splice site strength in multiple tissues. Pangolin outperforms
        state-of-the-art methods for predicting RNA splicing on a variety of prediction
        tasks. Pangolin improves prediction of the impact of genetic variants on RNA
        splicing, including common, rare, and lineage-specific genetic variation.
        In addition, Pangolin identifies loss-of-function mutations with high accuracy
        and recall, particularly for mutations that are not missense or nonsense,
        demonstrating remarkable potential for identifying pathogenic variants.
      authors:
      - name: Zeng T.
      - name: Li Y.I.
      citationCount: 52
      date: '2022-12-01T00:00:00Z'
      journal: Genome Biology
      title: Predicting RNA splicing from DNA sequence using Pangolin
    note: null
    pmcid: PMC9022248
    pmid: '35449021'
    type: []
    version: null
  relation: []
  toolType:
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  topic:
  - term: RNA splicing
    uri: http://edamontology.org/topic_3320
  - term: Genetic variation
    uri: http://edamontology.org/topic_0199
  - term: Gene transcripts
    uri: http://edamontology.org/topic_3512
  - term: RNA-Seq
    uri: http://edamontology.org/topic_3170
  - term: Exome sequencing
    uri: http://edamontology.org/topic_3676
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2024-02-29T15:44:00.705364Z'
  biotoolsCURIE: biotools:kMetaShot
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  credit:
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    fundrefid: null
    gridid: null
    name: Giuseppe Defazio
    note: Post-Doc Researcher at University of Bari
    orcidid: https://orcid.org/0000-0002-9356-5224
    rorid: null
    typeEntity: Person
    typeRole:
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    url: https://persone.ict.uniba.it/rubrica/@@cerca?advanced_search=False&sort_on=&SearchableText=defazio
  description: The application of 2nd and 3rd generation High Throughput Sequencing
    (HTS) technologies has deeply reshaped experimental method to investigate microbial
    communities and obtain a taxonomic and functional profile of the invetigated community.
    Shotgun Metagenomics allow to quickly obtain a representation of microorganisms
    genomes characterizing a particular environment. In order to obtain a fast e reliable
    taxonomic classification of microorganisms genomes we present kMetaShot, an alignment-free
    taxonomic classifier based on k-mer/minimizer counting.
  documentation:
  - note: null
    type:
    - Other
    url: https://github.com/gdefazio/kMetaShot
  download: []
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  license: GPL-3.0
  link: []
  maturity: Emerging
  name: kMetaShot
  operatingSystem:
  - Linux
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  owner: gdefazio
  publication:
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    metadata: null
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType:
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    uri: http://edamontology.org/topic_3174
  validated: 0
  version: []
- accessibility: null
  additionDate: '2026-07-17T04:45:01.899451Z'
  biotoolsCURIE: biotools:mtag
  biotoolsID: mtag
  collectionID: []
  confidence_flag: null
  cost: null
  credit: []
  description: mtag is a Python-based command line tool for jointly analyzing multiple
    sets of GWAS summary statistics as described by Turley et. al. (2018). It can
    also be used as a tool to meta-analyze GWAS results.
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/JonJala/mtag/wiki
  download: []
  editPermission:
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    type: public
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  function:
  - cmd: null
    input: []
    note: null
    operation:
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      uri: http://edamontology.org/operation_3209
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Nucleic acid sequence analysis
      uri: http://edamontology.org/operation_2478
    output: []
  homepage: https://github.com/JonJala/mtag
  homepage_status: 0
  language:
  - Perl
  - Python
  - R
  lastUpdate: '2026-07-17T04:45:01.902519Z'
  license: GPL-3.0
  link: []
  maturity: Mature
  name: mtag
  operatingSystem: []
  otherID: []
  owner: johangustafsson
  publication:
  - doi: 10.1038/s41588-017-0009-4
    metadata: null
    note: null
    pmcid: PMC5805593
    pmid: '29292387'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: GWAS study
    uri: http://edamontology.org/topic_3517
  validated: 0
  version:
  - 0.9.0
- accessibility: null
  additionDate: '2022-02-24T00:12:40.833213Z'
  biotoolsCURIE: biotools:mothur
  biotoolsID: mothur
  collectionID: []
  confidence_flag: null
  cost: null
  credit: []
  description: Open-source, platform-independent, community-supported software for
    describing and comparing microbial communities
  documentation:
  - note: null
    type:
    - User manual
    url: http://mothur.org/wiki/mothur_manual/
  - note: mothur Wiki page
    type:
    - Other
    url: http://mothur.org/wiki/
  download: []
  editPermission:
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  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: DNA barcoding
      uri: http://edamontology.org/operation_3200
    - term: Sequencing quality control
      uri: http://edamontology.org/operation_3218
    - term: Sequence clustering
      uri: http://edamontology.org/operation_0291
    - term: Taxonomic classification
      uri: http://edamontology.org/operation_3460
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    - term: Sequence read processing
      uri: http://edamontology.org/operation_3921
    - term: Phylogenetic analysis
      uri: http://edamontology.org/operation_0324
    output: []
  homepage: http://mothur.org/
  homepage_status: 0
  language:
  - C++
  lastUpdate: '2026-07-10T02:41:43.627271Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/mothur/mothur
  - note: mothur GitHub organization
    type:
    - Other
    - Repository
    url: https://github.com/mothur
  maturity: null
  name: mothur
  operatingSystem: []
  otherID: []
  owner: admin
  publication:
  - doi: 10.1128/aem.01541-09
    metadata:
      abstract: Mothur aims to be a comprehensive software package that allows users
        to use a single piece of software to analyze community sequence data. It builds
        upon previous tools to provide a flexible and powerful software package for
        analyzing sequencing data. As a case study, we used mothur to trim, screen,
        and align sequences; calculate distances; assign sequences to operational
        taxonomic units; and describe the α and β diversity of eight marine samples
        previously characterized by pyrosequencing of 16S rRNA gene fragments. This
        analysis of more than 222,000 sequences was completed in less than 2 h with
        a laptop computer. Copyright © 2009, American Society for Microbiology. All
        Rights Reserved.
      authors:
      - name: Schloss P.D.
      - name: Westcott S.L.
      - name: Ryabin T.
      - name: Hall J.R.
      - name: Hartmann M.
      - name: Hollister E.B.
      - name: Lesniewski R.A.
      - name: Oakley B.B.
      - name: Parks D.H.
      - name: Robinson C.J.
      - name: Sahl J.W.
      - name: Stres B.
      - name: Thallinger G.G.
      - name: Van Horn D.J.
      - name: Weber C.F.
      citationCount: 16666
      date: '2009-12-01T00:00:00Z'
      journal: Applied and Environmental Microbiology
      title: 'Introducing mothur: Open-source, platform-independent, community-supported
        software for describing and comparing microbial communities'
    note: null
    pmcid: PMC2786419
    pmid: '19801464'
    type: []
    version: null
  relation: []
  toolType:
  - Suite
  topic:
  - term: Microbial ecology
    uri: http://edamontology.org/topic_3697
  - term: Taxonomy
    uri: http://edamontology.org/topic_0637
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  - term: Phylogeny
    uri: http://edamontology.org/topic_0084
  validated: 0
  version: []
- accessibility: null
  additionDate: '2026-07-08T15:57:08.302197Z'
  biotoolsCURIE: biotools:thromboseq
  biotoolsID: thromboseq
  collectionID: []
  confidence_flag: null
  cost: null
  credit: []
  description: thromboSeq is a bioinformatics tool designed for the analysis of thrombosis-related
    sequencing data, providing functionalities for variant calling, annotation, and
    functional interpretation. It streamlines the processing of high-throughput sequencing
    data to identify genetic variants associated with thrombotic disorders.
  documentation: []
  download: []
  editPermission:
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  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Nucleic acid sequence
        uri: http://edamontology.org/data_2977
      format:
      - term: Gene expression report format
        uri: http://edamontology.org/format_2058
    note: null
    operation:
    - term: Data parsing
      uri: http://edamontology.org/operation_1812
    - term: Gene expression profiling
      uri: http://edamontology.org/operation_0314
    - term: Sequencing quality control
      uri: http://edamontology.org/operation_3218
    output:
    - data:
        term: Sequence report
        uri: http://edamontology.org/data_2955
      format: []
  homepage: https://github.com/MyronBest/thromboSeq_source_code
  homepage_status: 0
  language:
  - Shell
  - R
  - Perl
  lastUpdate: '2026-07-08T15:57:08.307883Z'
  license: GPL-3.0
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  maturity: Mature
  name: thromboSeq
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  publication:
  - doi: 10.3390/cancers13184644
    metadata: null
    note: null
    pmcid: PMC8468408
    pmid: '34572871'
    type:
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    version: null
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  additionDate: '2026-07-08T11:30:16.311175Z'
  biotoolsCURIE: biotools:qam
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  credit: []
  description: qam is a Python library and command-line tool to compute 3D surface-distances
    for evaluating liver ablation/tumor completeness based on segmentation images.
  documentation: []
  download: []
  editPermission:
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    type: private
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  function:
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    input:
    - data:
        term: Image
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      format: []
    note: null
    operation:
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      uri: http://edamontology.org/operation_3443
    - term: Calculation
      uri: http://edamontology.org/operation_3438
    output:
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        term: Plot
        uri: http://edamontology.org/data_2884
      format: []
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  homepage_status: 0
  language:
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  lastUpdate: '2026-07-08T11:30:16.314189Z'
  license: GPL-3.0
  link: []
  maturity: Mature
  name: qam
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  otherID: []
  owner: n.m.palmblad@lumc.nl
  publication:
  - doi: 10.3389/fonc.2021.623098
    metadata: null
    note: null
    pmcid: PMC7988092
    pmid: '33777768'
    type:
    - Primary
    version: null
  relation: []
  toolType:
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  - Library
  - Workflow
  topic:
  - term: Medical imaging
    uri: http://edamontology.org/topic_3384
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2026-06-29T09:42:44.084698Z'
  biotoolsCURIE: biotools:panabyss
  biotoolsID: panabyss
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: fabien.graziani@inrae.fr
    fundrefid: null
    gridid: null
    name: Graziani
    note: null
    orcidid: https://orcid.org/0009-0002-3966-0906
    rorid: null
    typeEntity: Institute
    typeRole:
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    url: null
  description: PanAbyss is a tool for exploring and visualizing pangenome graphs.
    It allows users to search for and display regions of a pangenome using coordinates
    on a reference individual or based on annotations. It also enables searching for
    regions associated with a selected set of individuals (for example, those linked
    to a phenotype), computing proximity trees, and retrieving sequences from a given
    region.
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/Pange31/PanAbyss/wiki
  download: []
  editPermission:
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    type: private
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  elixirNode:
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  elixirPlatform: []
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  homepage: https://github.com/Pange31/PanAbyss
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  lastUpdate: '2026-06-29T09:42:44.086988Z'
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  maturity: Emerging
  name: PanAbyss
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  name: MetaProteomeAnalyzer-Cloud
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  - term: Metaproteomics
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  - term: Proteomics
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  description: A comprehensive R package for identifying and ranking influential nodes
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      Feature prioritization and ranking

      Network reconstruction

      Biomarker candidate discovery

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  description: Finds SNP sites from a multi-FASTA alignment file.
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  function:
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  biotoolsCURIE: biotools:parsesnp21-26
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  description: A small <720Kb C++ windows utility. That allows you to load  Ancestry,
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  name: ParseSNP
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  description: CompuCell3D is a multiscale multicellular virtual tissue modeling and
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  description: NuclearPhaser is a method for phasing of dikaryotic genomes into the
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    metadata: null
    note: 'B.C. Haller, P.W. Messer. (2019). SLiM 3: Forward genetic simulations beyond
      the Wright–Fisher Model. Molecular Biology and Evolution 36(3), 632–637.'
    pmcid: PMC6389312
    pmid: '30517680'
    type:
    - Primary
    version: '3.0'
  - doi: 10.1093/molbev/msy237
    metadata: null
    note: B.C. Haller, P.W. Messer. (2019). Evolutionary modeling in SLiM 3 for beginners.
      Molecular Biology and Evolution 36(5), 1101–1109.
    pmcid: PMC6501880
    pmid: '30590560'
    type:
    - Method
    version: '3.0'
  - doi: 10.1111/1755-0998.12968
    metadata: null
    note: B.C. Haller, J. Galloway, J. Kelleher, P.W. Messer, P.L. Ralph. (2019).
      Tree-sequence recording in SLiM opens new horizons for forward-time simulation
      of whole genomes. Molecular Ecology Resources 19(2), 552–566.
    pmcid: PMC6393187
    pmid: '30565882'
    type:
    - Primary
    version: '3.0'
  - doi: 10.1101/2025.08.07.669155
    metadata: null
    note: 'BC Haller, PL Ralph, PW Messer. (2025). SLiM 5: Eco-evolutionary simulations
      across multiple chromosomes and full genomes. bioRxiv, 2025.08. 07.669155'
    pmcid: PMC12363870
    pmid: '40832315'
    type:
    - Primary
    version: '5.0'
  - doi: 10.1086/723601
    metadata: null
    note: 'B.C. Haller, P.W. Messer. (2023). SLiM 4: Multispecies eco-evolutionary
      modeling. The American Naturalist 201(5), E127–E139.'
    pmcid: PMC10793872
    pmid: '37130229'
    type:
    - Primary
    version: '4.0'
  relation: []
  toolType:
  - Command-line tool
  - Desktop application
  topic:
  - term: Ecology
    uri: http://edamontology.org/topic_0610
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  - term: Genetic variation
    uri: http://edamontology.org/topic_0199
  - term: Evolutionary biology
    uri: http://edamontology.org/topic_3299
  validated: 0
  version:
  - '5.2'
- accessibility: null
  additionDate: '2017-08-20T17:18:10Z'
  biotoolsCURIE: biotools:provean
  biotoolsID: provean
  collectionID:
  - Animal and Crop Genomics
  confidence_flag: null
  cost: null
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://provean.jcvi.org/contact.php
  description: A software tool which predicts whether an amino acid substitution or
    indel has an impact on the biological function of a protein.
  documentation:
  - note: null
    type:
    - General
    url: http://provean.jcvi.org/index.php
  download: []
  editPermission:
    authors:
    - animalandcropgenomics
    - ahmad_raza
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  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Sequence annotation
      uri: http://edamontology.org/operation_0361
    - term: Genetic variation analysis
      uri: http://edamontology.org/operation_3197
    output: []
  homepage: http://provean.jcvi.org/index.php
  homepage_status: 0
  language:
  - Shell
  lastUpdate: '2026-03-30T09:22:11.430833Z'
  license: GPL-3.0
  link: []
  maturity: null
  name: PROVEAN
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: ahmad_raza
  publication:
  - doi: 10.1371/journal.pone.0046688
    metadata:
      abstract: As next-generation sequencing projects generate massive genome-wide
        sequence variation data, bioinformatics tools are being developed to provide
        computational predictions on the functional effects of sequence variations
        and narrow down the search of casual variants for disease phenotypes. Different
        classes of sequence variations at the nucleotide level are involved in human
        diseases, including substitutions, insertions, deletions, frameshifts, and
        non-sense mutations. Frameshifts and non-sense mutations are likely to cause
        a negative effect on protein function. Existing prediction tools primarily
        focus on studying the deleterious effects of single amino acid substitutions
        through examining amino acid conservation at the position of interest among
        related sequences, an approach that is not directly applicable to insertions
        or deletions. Here, we introduce a versatile alignment-based score as a new
        metric to predict the damaging effects of variations not limited to single
        amino acid substitutions but also in-frame insertions, deletions, and multiple
        amino acid substitutions. This alignment-based score measures the change in
        sequence similarity of a query sequence to a protein sequence homolog before
        and after the introduction of an amino acid variation to the query sequence.
        Our results showed that the scoring scheme performs well in separating disease-associated
        variants (n = 21,662) from common polymorphisms (n = 37,022) for UniProt human
        protein variations, and also in separating deleterious variants (n = 15,179)
        from neutral variants (n = 17,891) for UniProt non-human protein variations.
        In our approach, the area under the receiver operating characteristic curve
        (AUC) for the human and non-human protein variation datasets is ~0.85. We
        also observed that the alignment-based score correlates with the deleteriousness
        of a sequence variation. In summary, we have developed a new algorithm, PROVEAN
        (Protein Variation Effect Analyzer), which provides a generalized approach
        to predict the functional effects of protein sequence variations including
        single or multiple amino acid substitutions, and in-frame insertions and deletions.
        The PROVEAN tool is available online at http://provean.jcvi.org. © 2012 Choi
        et al.
      authors:
      - name: Choi Y.
      - name: Sims G.E.
      - name: Murphy S.
      - name: Miller J.R.
      - name: Chan A.P.
      citationCount: 2199
      date: '2012-10-08T00:00:00Z'
      journal: PLoS ONE
      title: Predicting the Functional Effect of Amino Acid Substitutions and Indels
    note: null
    pmcid: PMC3466303
    pmid: '23056405'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  - term: Protein variants
    uri: http://edamontology.org/topic_3120
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2026-03-26T02:15:51.819440Z'
  biotoolsCURIE: biotools:quac
  biotoolsID: quac
  collectionID:
  - Sequencing
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Manavalan Gajapathy
    note: null
    orcidid: https://orcid.org/0000-0002-8606-0113
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://github.com/ManavalanG
  description: QuaC is a snakemake-based pipeline that runs several QC tools for WGS/WES
    samples and then summarizes their results using pre-defined, configurable QC thresholds.
  documentation:
  - note: null
    type:
    - General
    url: https://quac.readthedocs.io/
  download:
  - note: null
    type: Source code
    url: https://github.com/uab-cgds-worthey/quac/releases/tag/2.0
    version: '2.0'
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  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Sequencing quality control
      uri: http://edamontology.org/operation_3218
    output: []
  homepage: https://github.com/uab-cgds-worthey/quac
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2026-03-28T20:53:47.092010Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/uab-cgds-worthey/quac
  maturity: Mature
  name: quac
  operatingSystem: []
  otherID: []
  owner: sdhutchins
  publication:
  - doi: 10.21105/joss.05313
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  validated: 0
  version:
  - '2.0'
- accessibility: null
  additionDate: '2026-01-21T04:19:22.375410Z'
  biotoolsCURIE: biotools:rosalution
  biotoolsID: rosalution
  collectionID:
  - Rare Disease
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Angelina Uno-Antonison
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: https://github.com/SeriousHorncat
  description: Rosalution assists researchers study genetic variation 🧬 in patients
    🧑🏾‍🤝‍🧑🏼 by helping select candidate animal models 🐀🐁🐠🪱 to replicate the variation
    to further research to derive, diagnose, and provide therapies for ultra-rare
    diseases. Developed by the UAB Center for Computational Genomics and Data Science
    (CGDS).
  documentation: []
  download:
  - note: null
    type: Source code
    url: https://github.com/uab-cgds-worthey/rosalution/releases/tag/0.8.8-er
    version: 0.8.8-er
  editPermission:
    authors: []
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  elixir_badge: 0
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  homepage: https://github.com/uab-cgds-worthey/rosalution
  homepage_status: 0
  language:
  - JavaScript
  - Python
  lastUpdate: '2026-03-26T19:36:53.927081Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/uab-cgds-worthey/rosalution
  - note: null
    type:
    - Issue tracker
    url: https://github.com/uab-cgds-worthey/rosalution/issues
  maturity: Mature
  name: Rosalution
  operatingSystem: []
  otherID: []
  owner: sdhutchins
  publication:
  - doi: 10.21105/joss.05443
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Genetic variation
    uri: http://edamontology.org/topic_0199
  validated: 0
  version:
  - 0.8.8-er
- accessibility: Open access
  additionDate: '2018-12-12T12:35:31Z'
  biotoolsCURIE: biotools:bio.tools
  biotoolsID: bio.tools
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Contributors
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: https://biotools.readthedocs.io/en/latest/contributors.html
  description: The community registry of computational tools and data resources for
    biosciences.
  documentation:
  - note: API usage guide
    type:
    - API documentation
    url: https://biotools.readthedocs.io/en/latest/api_usage_guide.html
  - note: API Reference
    type:
    - API documentation
    url: https://biotools.readthedocs.io/en/latest/api_reference.html
  - note: null
    type:
    - Citation instructions
    url: https://biotools.readthedocs.io/en/latest/publications.html#citation
  - note: null
    type:
    - Contributions policy
    url: https://biotools.readthedocs.io/en/latest/contributors_guide.html
  - note: null
    type:
    - General
    url: https://biotools.readthedocs.io/en/latest/
  - note: null
    type:
    - Governance
    url: https://biotools.readthedocs.io/en/latest/governance.html
  - note: Curators Guide
    type:
    - User manual
    url: https://biotools.readthedocs.io/en/latest/curators_guide.html
  download:
  - note: null
    type: Source code
    url: https://github.com/bio-tools/biotoolsRegistry
    version: null
  editPermission:
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    - hans
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  elixirNode:
  - Denmark
  elixirPlatform:
  - Tools
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Text
        uri: http://edamontology.org/data_3671
      format:
      - term: plain text format (unformatted)
        uri: http://edamontology.org/format_1964
    note: null
    operation:
    - term: Data retrieval
      uri: http://edamontology.org/operation_2422
    output:
    - data:
        term: Tool metadata
        uri: http://edamontology.org/data_0958
      format:
      - term: YAML
        uri: http://edamontology.org/format_3750
      - term: JSON
        uri: http://edamontology.org/format_3464
      - term: XML
        uri: http://edamontology.org/format_2332
  homepage: https://bio.tools
  homepage_status: 0
  language:
  - JavaScript
  - Python
  lastUpdate: '2026-03-25T12:24:23.606945Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Helpdesk
    url: https://biotools.readthedocs.io/en/latest/support.html?highlight=help
  - note: null
    type:
    - Issue tracker
    url: https://github.com/bio-tools/biotoolsregistry/issues
  - note: null
    type:
    - Mailing list
    url: https://biotools.readthedocs.io/en/latest/contributors_guide.html#mailing-list
  - note: null
    type:
    - Repository
    url: https://github.com/bio-tools/biotoolsregistry/
  maturity: Emerging
  name: bio.tools
  operatingSystem: []
  otherID:
  - type: rrid
    value: RRID:SCR_014695
    version: null
  owner: jison
  publication:
  - doi: 10.1093/nar/gkv1116
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  - doi: 10.12688/f1000research.12974.1
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Other
    version: null
  - doi: 10.1093/gigascience/gix022
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Other
    version: null
  - doi: 10.1007/s10009-015-0392-z
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Other
    version: null
  relation: []
  toolType:
  - Web API
  - Database portal
  - Web application
  topic:
  - term: Ontology and terminology
    uri: http://edamontology.org/topic_0089
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  - term: Data curation and archival
    uri: http://edamontology.org/topic_0219
  - term: Computational biology
    uri: http://edamontology.org/topic_3307
  validated: 1
  version: []
- accessibility: null
  additionDate: '2021-11-29T10:31:42.544157Z'
  biotoolsCURIE: biotools:rhizovision-explorer
  biotoolsID: rhizovision-explorer
  collectionID: []
  confidence_flag: tool
  cost: null
  credit:
  - email: lmyork@noble.org
    fundrefid: null
    gridid: null
    name: Larry M. York
    note: null
    orcidid: https://orcid.org/0000-0002-1995-9479
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: RhizoVision Explorer is free and open-source software developed for
    estimating root traits from images acquired from a flatbed scanner or camera.
    Root images are expected to have a high contrast of roots with the background,
    homogenous lighting, and minimal overlapping of roots.
  documentation: []
  download: []
  editPermission:
    authors:
    - RDKing
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Image analysis
      uri: http://edamontology.org/operation_3443
    - term: Standardisation and normalisation
      uri: http://edamontology.org/operation_3435
    - term: Feature extraction
      uri: http://edamontology.org/operation_3937
    output: []
  homepage: https://github.com/noble-research-institute/RhizoVisionExplorer
  homepage_status: 0
  language:
  - C++
  lastUpdate: '2026-03-17T09:34:03.454691Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Issue tracker
    url: https://github.com/rootphenomicslab/RhizoVisionExplorer/issues
  maturity: null
  name: RhizoVision Explorer
  operatingSystem: []
  otherID: []
  owner: Kigaard
  publication:
  - doi: 10.1093/aobpla/plab056
    metadata:
      abstract: Roots are central to the function of natural and agricultural ecosystems
        by driving plant acquisition of soil resources and influencing the carbon
        cycle. Root characteristics like length, diameter and volume are critical
        to measure to understand plant and soil functions. RhizoVision Explorer is
        an open-source software designed to enable researchers interested in roots
        by providing an easy-To-use interface, fast image processing and reliable
        measurements. The default broken roots mode is intended for roots sampled
        from pots and soil cores, washed and typically scanned on a flatbed scanner,
        and provides measurements like length, diameter and volume. The optional whole
        root mode for complete root systems or root crowns provides additional measurements
        such as angles, root depth and convex hull. Both modes support providing measurements
        grouped by defined diameter ranges, the inclusion of multiple regions of interest
        and batch analysis. RhizoVision Explorer was successfully validated against
        ground truth data using a new copper wire image set. In comparison, the current
        reference software, the commercial WinRhizo™, drastically underestimated volume
        when wires of different diameters were in the same image. Additionally, measurements
        were compared with WinRhizo™ and IJ_Rhizo using a simulated root image set,
        showing general agreement in software measurements, except for root volume.
        Finally, scanned root image sets acquired in different labs for the crop,
        herbaceous and tree species were used to compare results from RhizoVision
        Explorer with WinRhizo™. The two software showed general agreement, except
        that WinRhizo™ substantially underestimated root volume relative to RhizoVision
        Explorer. In the current context of rapidly growing interest in root science,
        RhizoVision Explorer intends to become a reference software, improve the overall
        accuracy and replicability of root trait measurements and provide a foundation
        for collaborative improvement and reliable access to all.
      authors:
      - name: Seethepalli A.
      - name: Dhakal K.
      - name: Griffiths M.
      - name: Guo H.
      - name: Freschet G.T.
      - name: York L.M.
      citationCount: 130
      date: '2021-12-01T00:00:00Z'
      journal: AoB PLANTS
      title: 'RhizoVision Explorer: Open-source software for root image analysis and
        measurement standardization'
    note: null
    pmcid: PMC8598384
    pmid: '34804466'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Desktop application
  topic:
  - term: Agricultural science
    uri: http://edamontology.org/topic_3810
  - term: Imaging
    uri: http://edamontology.org/topic_3382
  - term: Plant biology
    uri: http://edamontology.org/topic_0780
  - term: Phenomics
    uri: http://edamontology.org/topic_3298
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2026-03-16T11:37:02.408710Z'
  biotoolsCURIE: biotools:Freezing-Point
  biotoolsID: Freezing-Point
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit: []
  description: Freezing-Point is a user-friendly open-source software for the automated
    analysis of freezing behavior in rodents. Based on recorded videos or pose estimation
    files. An adaptive, data-driven algorithm automatically determines freezing detection
    thresholds, reducing subjective bias while preserving user oversight. Freezing-Point
    adopts a user-oriented design centered on a graphical interface that provides
    continuous visual access to original data, processing steps and analysis results.
    This design enables users to inspect, validate or refine results while minimizing
    unnecessary data manipulation.
  documentation:
  - note: null
    type:
    - Quick start guide
    url: https://github.com/gillescourtand/Freezing-Point/blob/main/Doc/User_guide.md
  download:
  - note: null
    type: Binaries
    url: https://github.com/gillescourtand/Freezing-Point/releases
    version: 1.0.2
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    type: private
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  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Quantification
      uri: http://edamontology.org/operation_3799
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Optimisation and refinement
      uri: http://edamontology.org/operation_2425
    output: []
  homepage: https://github.com/gillescourtand/Freezing-Point
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2026-03-16T11:37:02.410724Z'
  license: GPL-3.0
  link: []
  maturity: Mature
  name: Freezing-Point
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: gilles.courtand
  publication: []
  relation: []
  toolType:
  - Desktop application
  topic:
  - term: Neurobiology
    uri: http://edamontology.org/topic_3304
  validated: 0
  version:
  - 1.0.2
- accessibility: Open access
  additionDate: '2016-03-17T13:51:10Z'
  biotoolsCURIE: biotools:webnma
  biotoolsID: webnma
  collectionID:
  - BiB tools
  - CBU tools
  - UiB tools
  - ELIXIR-NO
  - ELIXIR-Norway
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: Nathalie.Reuter@uib.no
    fundrefid: null
    gridid: null
    name: Nathalie Reuter
    note: null
    orcidid: https://orcid.org/0000-0002-3649-7675
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    - Developer
    url: http://www.cbu.uib.no/reuter/
  - email: null
    fundrefid: null
    gridid: null
    name: Sandhya P Tiwari
    note: null
    orcidid: https://orcid.org/0000-0002-0747-3826
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Kidane M Tekle
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Tristan Cragnolini
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Svenn H Grindhaug
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Lars Skjærven
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Gisle Salensminde
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Edvin Fuglebakk
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Siv M Hollup
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Department of Molecular Biology, University of Bergen, Norway
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Computational Biology Unit, Department of Informatics, University of Bergen,
      Norway
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: UiB
    note: null
    orcidid: null
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    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  description: WEBnm@ provides quick, automated computation and analysis of low-frequency
    normal modes for protein structures.
  documentation:
  - note: null
    type:
    - Quick start guide
    url: http://apps.cbu.uib.no/webnma3/howto/single
  - note: null
    type:
    - FAQ
    url: http://apps.cbu.uib.no/webnma3/qanda
  - note: null
    type:
    - General
    - Citation instructions
    url: http://apps.cbu.uib.no/webnma3/about
  download: []
  editPermission:
    authors:
    - eca008
    - korbinib
    type: group
  elixirCommunity:
  - 3D-BioInfo
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  - Norway
  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: Constructs elastic network model from alpha carbon coordinates of the protein,
      and computes properties to describe large scale conformations. Computes normal
      modes, fluctuation profiles, inter-residue correlations, conformational overlap
      analysis and vector field representations. Structural amino acid profiles, and
      normal mode characteristics describing protein motion, visualized in plots and
      decorated structure visualizations. White space delimited tabular data for normal
      modes and the provided plots
    operation:
    - term: Structure visualisation
      uri: http://edamontology.org/operation_0570
    - term: Protein flexibility and motion analysis
      uri: http://edamontology.org/operation_0244
    output:
    - data:
        term: Plot
        uri: http://edamontology.org/data_2884
      format:
      - term: PDF
        uri: http://edamontology.org/format_3508
    - data:
        term: Sequence profile
        uri: http://edamontology.org/data_1354
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
  - cmd: null
    input:
    - data:
        term: Structure alignment
        uri: http://edamontology.org/data_0886
      format:
      - term: FASTA-like (text)
        uri: http://edamontology.org/format_2200
    - data:
        term: Protein structure
        uri: http://edamontology.org/data_1460
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
    note: Performs comparative analysis of the normal modes of protein structures.
      Computes the Bhattacharyya Coefficient (BC) and the Root Mean Squared Inner
      Product (RMSIP) of aligned parts of the proteins. Alignment of sets of proteins
      to be compared. Multiple protein structures Heatmaps, dendrograms and structural
      amino acid profiles for visual comparison of structural similarity. White space
      delimited tabular data for the provided plots
    operation:
    - term: Protein structure comparison
      uri: http://edamontology.org/operation_2487
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    output:
    - data:
        term: Plot
        uri: http://edamontology.org/data_2884
      format:
      - term: PDF
        uri: http://edamontology.org/format_3508
    - data:
        term: Structural profile
        uri: http://edamontology.org/data_0889
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
  homepage: http://apps.cbu.uib.no/webnma
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2026-03-11T08:56:55.566213Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    - Issue tracker
    url: https://github.com/reuter-group/webnma3
  - note: Helpdesk and support for ELIXIR Norway services.
    type:
    - Helpdesk
    url: https://elixir.no/helpdesk
  maturity: Mature
  name: WEBnma
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: UiB
  publication:
  - doi: 10.1186/s12859-014-0427-6
    metadata:
      abstract: 'Background: Normal mode analysis (NMA) using elastic network models
        is a reliable and cost-effective computational method to characterise protein
        flexibility and by extension, their dynamics. Further insight into the dynamics-function
        relationship can be gained by comparing protein motions between protein homologs
        and functional classifications. This can be achieved by comparing normal modes
        obtained from sets of evolutionary related proteins. Results: We have developed
        an automated tool for comparative NMA of a set of pre-aligned protein structures.
        The user can submit a sequence alignment in the FASTA format and the corresponding
        coordinate files in the Protein Data Bank (PDB) format. The computed normalised
        squared atomic fluctuations and atomic deformation energies of the submitted
        structures can be easily compared on graphs provided by the web user interface.
        The web server provides pairwise comparison of the dynamics of all proteins
        included in the submitted set using two measures: the Root Mean Squared Inner
        Product and the Bhattacharyya Coefficient. The Comparative Analysis has been
        implemented on our web server for NMA, WEBnmat, which also provides recently
        upgraded functionality for NMA of single protein structures. This includes
        new visualisations of protein motion, visualisation of inter-residue correlations
        and the analysis of conformational change using the. In addition, programmatic
        access to WEBnmat is now available through a SOAP-based web service. WEBnmat
        is available at. Conclusion: WEBnmat v2.0 is an online tool offering unique
        capability for comparative NMA on multiple protein structures. Along with
        a convenient web interface, powerful computing resources, and several methods
        for mode analyses, WEBnmat facilitates the assessment of protein flexibility
        within protein families and superfamilies. These analyses can give a good
        view of how the structures move and how the flexibility is conserved over
        the different structures.'
      authors:
      - name: Tiwari S.P.
      - name: Fuglebakk E.
      - name: Hollup S.M.
      - name: Skjaerven L.
      - name: Cragnolini T.
      - name: Grindhaug S.H.
      - name: Tekle K.M.
      - name: Reuter N.
      citationCount: 87
      date: '2014-12-30T00:00:00Z'
      journal: BMC Bioinformatics
      title: 'WEBnmat v2.0: Web server and services for comparing protein flexibility'
    note: null
    pmcid: PMC4339738
    pmid: '25547242'
    type:
    - Primary
    version: '2.0'
  - doi: 10.1186/1471-2105-6-52
    metadata:
      abstract: 'Background: Normal mode analysis (NMA) has become the method of choice
        to investigate the slowest motions in macromolecular systems. NMA is especially
        useful for large biomolecular assemblies, such as transmembrane channels or
        virus capsids. NMA relies on the hypothesis that the vibrational normal modes
        having the lowest frequencies (also named soft modes) describe the largest
        movements in a protein and are the ones that are functionally relevant. Results:
        We developed a web-based server to perform normal modes calculations and different
        types of analyses. Starting from a structure file provided by the user in
        the PDB format, the server calculates the normal modes and subsequently offers
        the user a series of automated calculations; normalized squared atomic displacements,
        vector field representation and animation of the first six vibrational modes.
        Each analysis is performed independently from the others and results can be
        visualized using only a web browser. No additional plug-in or software is
        required. For users who would like to analyze the results with their favorite
        software, raw results can also be downloaded. The application is available
        on http://www.bioinfo.no/tools/normalmodes. We present here the underlying
        theory, the application architecture and an illustration of its features using
        a large transmembrane protein as an example. Conclusion: We built an efficient
        and modular web application for normal mode analysis of proteins. Non specialists
        can easily and rapidly evaluate the degree of flexibility of multi-domain
        protein assemblies and characterize the large amplitude movements of their
        domains. © 2005 Hollup et al; licensee BioMed Central Ltd.'
      authors:
      - name: Hollup S.M.
      - name: Salensminde G.
      - name: Reuter N.
      citationCount: 105
      date: '2005-03-11T00:00:00Z'
      journal: BMC Bioinformatics
      title: 'WEBnm@: A web application for normal mode analyses of proteins'
    note: null
    pmcid: PMC1274249
    pmid: '15762993'
    type:
    - Primary
    version: '1.0'
  relation:
  - biotoolsID: numpy
    type: uses
  - biotoolsID: biopython
    type: uses
  - biotoolsID: matplotlib
    type: uses
  - biotoolsID: mustang
    type: uses
  - biotoolsID: dssp
    type: uses
  toolType:
  - Web API
  - Suite
  topic:
  - term: Protein structure analysis
    uri: http://edamontology.org/topic_2814
  - term: Protein folds and structural domains
    uri: http://edamontology.org/topic_0736
  validated: 1
  version:
  - '3.5'
- accessibility: null
  additionDate: '2019-09-27T09:58:46Z'
  biotoolsCURIE: biotools:BioMercator
  biotoolsID: BioMercator
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: BioMercator is a software that provides a complete set of algorithms
    and visualization tool covering all steps required to perform QTL meta-analysis,
    graphical representation of large datasets. User may import sequence and genome
    annotations datasets within the software in order to display functional annotation
    related to QTL and meta-QTL.
  documentation: []
  download:
  - note: null
    type: Binaries
    url: https://sourcesup.renater.fr/frs/?group_id=2301
    version: 4.2.3
  editPermission:
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  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: QTL map
        uri: http://edamontology.org/data_1860
      format:
      - term: XML
        uri: http://edamontology.org/format_2332
      - term: Textual format
        uri: http://edamontology.org/format_2330
    - data:
        term: Genome map
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      format:
      - term: GFF3
        uri: http://edamontology.org/format_1975
    note: null
    operation:
    - term: Genetic mapping
      uri: http://edamontology.org/operation_0282
    - term: Physical mapping
      uri: http://edamontology.org/operation_2944
    output: []
  homepage: https://sourcesup.renater.fr/projects/biomercator
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2026-03-11T08:56:54.859634Z'
  license: GPL-3.0
  link: []
  maturity: Mature
  name: BioMercator
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: admin
  publication:
  - doi: 10.1093/bioinformatics/bth230
    metadata:
      abstract: 'Summary: Breeding programs face the challenge of integrating information
        from genomics and from quantitative trait loci (QTL) analysis in order to
        identify genomic sequences controlling the variation of important traits.
        Despite the development of integrative databases, building a consensus map
        of genes, QTL and other loci gathered from multiple maps remains a manual
        and tedious task. Nevertheless, this is a critical step to reveal co-locations
        between genes and QTL. Another important matter is to determine whether QTL
        linked to same traits or related ones is detected in independent experiments
        and located in the same region, and represents a single locus or not. Statistical
        tools such as meta-analysis can be used to answer this question. BioMercator
        has been developed to automate map compilation and QTL meta-analysis, and
        to visualize co-locations between genes and QTL through a graphical interface.
        © Oxford University Press 2004; all rights reserved.'
      authors:
      - name: Arcade A.
      - name: Labourdette A.
      - name: Falque M.
      - name: Mangin B.
      - name: Chardon F.
      - name: Charcosset A.
      - name: Joets J.
      citationCount: 382
      date: '2004-09-22T00:00:00Z'
      journal: Bioinformatics
      title: 'BioMercator: Integrating genetic maps and QTL towards discovery of candidate
        genes'
    note: null
    pmcid: null
    pmid: '15059820'
    type: []
    version: '3'
  relation: []
  toolType:
  - Desktop application
  topic:
  - term: Quantitative genetics
    uri: http://edamontology.org/topic_3055
  - term: Plant biology
    uri: http://edamontology.org/topic_0780
  validated: 1
  version:
  - 4.2.3
- accessibility: null
  additionDate: '2023-05-22T15:10:32.141196Z'
  biotoolsCURIE: biotools:bigseqkit
  biotoolsID: bigseqkit
  collectionID: []
  confidence_flag: null
  cost: null
  credit: []
  description: The Next Generation Sequencing (NGS) raw data are stored in FASTA and
    FASTQ text-based file formats. Common operations on FASTA/Q files include searching,
    filtering, sampling, deduplication and sorting, among others. We can find several
    tools in the literature for FASTA/Q file manipulation but none of them are well
    fitted for large files of tens of GB (likely TBs in the near future) since mostly
    they are based on sequential processing. The exception is seqkit that allows some
    routines to use a few threads but, in any case, the scalability is very limited.
    To deal with this issue, we introduce BigSeqKit, a parallel toolkit to manipulate
    FASTA/Q files at scale with speed and scalability at its core. BigSeqKit takes
    advantage of an HPC-Big Data framework (IgnisHPC) to parallelize and optimize
    the commands included in seqkit. In this way, in most cases it is from tens to
    hundreds of times faster than other state-of-the-art tools such as seqkit, samtools
    and pyfastx.
  documentation: []
  download: []
  editPermission:
    authors: []
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  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: DNA sequence
        uri: http://edamontology.org/data_3494
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: null
    operation:
    - term: Sequence trimming
      uri: http://edamontology.org/operation_3192
    - term: DNA transcription
      uri: http://edamontology.org/operation_0372
    - term: DNA translation
      uri: http://edamontology.org/operation_0371
    - term: Sequence conversion
      uri: http://edamontology.org/operation_0233
    output:
    - data:
        term: DNA sequence
        uri: http://edamontology.org/data_3494
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
      - term: FASTA
        uri: http://edamontology.org/format_1929
  homepage: https://github.com/citiususc/BigSeqKit
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2026-03-01T11:28:15.208151Z'
  license: GPL-3.0
  link: []
  maturity: null
  name: BigSeqKit
  operatingSystem:
  - Linux
  otherID: []
  owner: cesarpomar
  publication: []
  relation: []
  toolType:
  - Library
  - Command-line tool
  topic:
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2021-05-06T06:18:52Z'
  biotoolsCURIE: biotools:pangenome-blast
  biotoolsID: pangenome-blast
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Bielefeld University
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: https://www.uni-bielefeld.de/
  - email: null
    fundrefid: null
    gridid: null
    name: Genome Informatics
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: https://gi.cebitec.uni-bielefeld.de/
  - email: plast-service@cebitec.uni-bielefeld.de
    fundrefid: null
    gridid: null
    name: Tizian Schulz
    note: null
    orcidid: https://orcid.org/0000-0003-0744-7078
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  description: PLAST is a heuristical method to search for highest scoring local alignments
    between a DNA sequence query and a graphical pangenome. It takes as input a plain
    DNA sequence and a pangenome which may either be a set of (multiple) FASTA or
    FASTQ files or a sequence graph constructed by the tool Bifrost. It then outputs
    statistically meaningful (gapped) alignments in the style of the NCBI BLAST standard
    output format. Alignments are calculated based on a "seed-and-extend approach"
    while traversing the sequence graph. Biologically meaningful alignments are filtered
    by using an alignment statistic explicitly developed for sequence-to-graph alignments
    involving graphical pangenomes.
  documentation:
  - note: null
    type:
    - General
    url: https://gitlab.ub.uni-bielefeld.de/gi/plast/-/blob/master/README.md
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: PLAST Search -i pangenomeGraphCommonFilePrefix -q fileContainingOneQueryPerLine
    input:
    - data:
        term: DNA sequence
        uri: http://edamontology.org/data_3494
      format:
      - term: unambiguous pure nucleotide
        uri: http://edamontology.org/format_1211
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: GFA 1
        uri: http://edamontology.org/format_3975
      - term: Binary format
        uri: http://edamontology.org/format_2333
    note: "In order to search for alignments within the pangenome graph, \nA pangenome\
      \ graph used to search for alignments consists of (1) a file in GFA format containing\
      \ all sequences of the graph, (2) a binary file produced by the tool itself\
      \ or the software \"Bifrost\" and (3) a program-specific index data structure\
      \ in binary format."
    operation:
    - term: Local alignment
      uri: http://edamontology.org/operation_0495
    output:
    - data:
        term: Nucleic acid sequence alignment
        uri: http://edamontology.org/data_1383
      format:
      - term: BLAST results
        uri: http://edamontology.org/format_1333
  - cmd: PLAST Build -i pangenomeGraphCommonFilePrefix -R *.fasta
    input:
    - data:
        term: Sequence set
        uri: http://edamontology.org/data_0850
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
      - term: FASTQ
        uri: http://edamontology.org/format_1930
    note: If a pangenome graph already exists and only an index has to be built, FASTA/FASTQ
      files are not needed.
    operation:
    - term: Indexing
      uri: http://edamontology.org/operation_0227
    output:
    - data:
        term: Sequence set
        uri: http://edamontology.org/data_0850
      format:
      - term: GFA 1
        uri: http://edamontology.org/format_3975
      - term: Binary format
        uri: http://edamontology.org/format_2333
  homepage: https://github.com/tischulz1/plast
  homepage_status: 0
  language:
  - C++
  lastUpdate: '2026-02-26T11:22:02.485629Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://gitlab.ub.uni-bielefeld.de/gi/plast
  - note: null
    type:
    - Mirror
    url: https://github.com/tischulz1/plast
  maturity: Mature
  name: PLAST
  operatingSystem:
  - Linux
  - Mac
  - Windows
  otherID: []
  owner: tizian
  publication:
  - doi: 10.1093/bioinformatics/btab077
    metadata:
      abstract: 'Motivation: Increasing amounts of individual genomes sequenced per
        species motivate the usage of pangenomic approaches. Pangenomes may be represented
        as graphical structures, e.g. compacted colored de Bruijn graphs, which offer
        a low memory usage and facilitate reference-free sequence comparisons. While
        sequence-to-graph mapping to graphical pangenomes has been studied for some
        time, no local alignment search tool in the vein of BLAST has been proposed
        yet. Results: We present a new heuristic method to find maximum scoring local
        alignments of a DNA query sequence to a pangenome represented as a compacted
        colored de Bruijn graph. Our approach additionally allows a comparison of
        similarity among sequences within the pangenome. We show that local alignment
        scores follow an exponential-tail distribution similar to BLAST scores, and
        we discuss how to estimate its parameters to separate local alignments representing
        sequence homology from spurious findings. An implementation of our method
        is presented, and its performance and usability are shown. Our approach scales
        sublinearly in running time and memory usage with respect to the number of
        genomes under consideration. This is an advantage over classical methods that
        do not make use of sequence similarity within the pangenome.'
      authors:
      - name: Schulz T.
      - name: Wittler R.
      - name: Rahmann S.
      - name: Hach F.
      - name: Stoye J.
      citationCount: 6
      date: '2021-08-15T00:00:00Z'
      journal: Bioinformatics
      title: Detecting high-scoring local alignments in pangenome graphs
    note: null
    pmcid: PMC8388040
    pmid: '33532821'
    type:
    - Primary
    - Method
    - Benchmarking study
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Comparative genomics
    uri: http://edamontology.org/topic_0797
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  validated: 0
  version:
  - 0.0.1-0.2.0
- accessibility: null
  additionDate: '2017-01-17T14:50:59Z'
  biotoolsCURIE: biotools:esiprot
  biotoolsID: esiprot
  collectionID:
  - ms-utils
  - Proteomics
  confidence_flag: null
  cost: null
  credit:
  - email: robert.winkler@ira.cinvestav.mx
    fundrefid: null
    gridid: null
    name: Robert Winkler
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Maintainer
    url: null
  - email: webmaster@ms-utils.org
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Documentor
    url: http://ms-utils.org
  description: Charge state determination and molecular weight calculation for low
    resolution electrospray ionization data.
  documentation:
  - note: null
    type:
    - General
    url: http://www.lababi.bioprocess.org/index.php/lababi-software/84-esiprot
  download:
  - note: null
    type: Source code
    url: http://www.bioprocess.org/esiprot/esiprot.zip
    version: null
  - note: null
    type: Source code
    url: http://www.bioprocess.org/esiprot/esiprot.zip
    version: null
  editPermission:
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  function:
  - cmd: null
    input:
    - data:
        term: Peptide mass fingerprint
        uri: http://edamontology.org/data_0944
      format:
      - term: Mass spectrometry data format
        uri: http://edamontology.org/format_3245
    note: null
    operation:
    - term: Protein molecular weight calculation
      uri: http://edamontology.org/operation_0398
    - term: Protein fragment weight comparison
      uri: http://edamontology.org/operation_2929
    - term: Deisotoping
      uri: http://edamontology.org/operation_3629
    output:
    - data:
        term: Peptide mass fingerprint
        uri: http://edamontology.org/data_0944
      format:
      - term: Mass spectrometry data format
        uri: http://edamontology.org/format_3245
  homepage: https://nube-gran.de/esiprot
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2026-02-24T10:43:29.547210Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Mirror
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    metadata:
      abstract: Electrospray ionization (ESI) ion trap mass spectrometers with relatively
        low resolution are frequently used for the analysis of natural products and
        peptides. Although ESI spectra of multiply charged protein molecules also
        can be measured on this type of devices, only average spectra are produced
        for the majority of naturally occurring proteins. Evaluating such ESI protein
        spectra would provide valuable information about the native state of investigated
        proteins. However, no suitable and freely available software could be found
        which allows the charge state determination and molecular weight calculation
        of single proteins from average ESI-MS data. Therefore, an algorithm based
        on standard deviation optimization (scatter minimization) was implemented
        for the analysis of protein ESI-MS data. The resulting software ESIprot was
        tested with ESI-MS data of six intact reference proteins between 12.4 and
        66.7kDa. In all cases, the correct charge states could be determined. The
        obtained absolute mass errors were in a range between -0.2 and 1.2Da, the
        relative errors below 30ppm. The possible mass accuracy allows for valid conclusions
        about the actual condition of proteins. Moreover, the ESIprot algorithm demonstrates
        an extraordinary robustness and allows spectral interpretation from as little
        as two peaks, given sufficient quality of the provided m/z data, without the
        necessity for peak intensity data. ESIprot is independent from the raw data
        format and the computer platform, making it a versatile tool for mass spectrometrists.
        The program code was released under the open-source GPLv3 license to support
        future developments of mass spectrometry software. © 2010 John Wiley & Sons,
        Ltd.
      authors:
      - name: Winkler R.
      citationCount: 75
      date: '2010-01-01T00:00:00Z'
      journal: Rapid Communications in Mass Spectrometry
      title: 'ESIprot: A universal tool for charge state determination and molecular
        weight calculation of proteins from electrospray ionization mass spectrometry
        data'
    note: null
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  description: kollaR is an open-source R library for eye-tracking analysis and visualization,
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    metadata: null
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  description: Pv3Rs is an R package that allows users to infer the cause (recrudescence,
    relapse, or reinfection) of Plasmodium vivax malaria recurrence using genetic
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    recurrence states and is freely available on CRAN under the GNU license.
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    metadata: null
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    uri: http://edamontology.org/topic_0625
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  - email: mr2022@medschl.cam.ac.uk
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  description: PSQAN is a Snakemake and R workflow designed to prioritize high-confidence
    and biologically relevant transcripts from long-read RNA sequencing data, facilitating
    the interpretation of transcript characterization results.
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  function:
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    operation:
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  topic:
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  description: RISK is a tool for biological network annotation and visualization
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    metadata: null
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  description: WatCon is a Python package for analyzing conserved water networks across
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