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        parameters, every genome needs dedicated gene finder. © 2004 Korf, licensee
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  - note: null
    type:
    - Repository
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  name: screen_assembly
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  otherID: []
  owner: aniehues
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  - doi: 10.1038/s41588-019-0417-8
    metadata: null
    note: null
    pmcid: PMC6650292
    pmid: '31133745'
    type:
    - Primary
    version: null
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  toolType:
  - Script
  - Command-line tool
  topic:
  - term: Sequence assembly
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  version:
  - v1
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  additionDate: '2026-02-22T13:39:14.055350Z'
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    name: Doga Cedden
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    typeEntity: Person
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    url: null
  - email: gbucher1@uni-goettingen.de
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    name: Gregor Bucher
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    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: dsRIP is a web platform for optimizing dsRNA sequences for RNAi in
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    and minimizing risk to non-target species, based on sequence features identified
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  publication:
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    metadata: null
    note: null
    pmcid: PMC12039203
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    type: []
    version: null
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  topic:
  - term: Functional, regulatory and non-coding RNA
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  - term: siRNA experiment
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  - term: Probes and primers
    uri: http://edamontology.org/topic_0632
  - term: Gene transcripts
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  - term: RNA-Seq
    uri: http://edamontology.org/topic_3170
  validated: 0
  version: []
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  additionDate: '2017-08-03T18:57:46Z'
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    typeEntity: Person
    typeRole:
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  description: A web application that provides many functionalities for improved PCR
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  - note: null
    type:
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  function:
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    output: []
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  language:
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  lastUpdate: '2026-06-04T08:07:29.277429Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
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  name: RExPrimer
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  owner: mbs_import
  publication:
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    metadata: null
    note: null
    pmcid: PMC2788391
    pmid: '19958502'
    type: []
    version: null
  relation: []
  toolType:
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  topic:
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    uri: http://edamontology.org/topic_3511
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  - term: Probes and primers
    uri: http://edamontology.org/topic_0632
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-05-16T13:43:29Z'
  biotoolsCURIE: biotools:phylip
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    name: Joe Felsenstein
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
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    url: http://evolution.gs.washington.edu/felsenstein.html
  description: Comprehensive set of programs for phylogenetic analyses; available
    for PC and Mac; source code available for easy compiling in UNIX.
  documentation:
  - note: null
    type:
    - General
    url: http://evolution.genetics.washington.edu/phylip/phylip.html
  download: []
  editPermission:
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  function:
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    operation:
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    output: []
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  language:
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  - Windows
  - Mac
  otherID:
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    version: null
  owner: ELIXIR-EE
  publication:
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    metadata:
      abstract: 'Background: Phylogenetic study of protein sequences provides unique
        and valuable insights into the molecular and genetic basis of important medical
        and epidemiological problems as well as insights about the origins and development
        of physiological features in present day organisms. Consensus phylogenies
        based on the bootstrap and other resampling methods play a crucial part in
        analyzing the robustness of the trees produced for these analyses. Methodology:
        Our focus was to increase the number of bootstrap replications that can be
        performed on large protein datasets using the maximum parsimony, distance
        matrix, and maximum likelihood methods. We have modified the PHYLIP package
        using MPI to enable large-scale phylogenetic study of protein sequences, using
        a statistically robust number of bootstrapped datasets, to be performed in
        a moderate amount of time. This paper discusses the methodology used to parallelize
        the PHYLIP programs and reports the performance of the parallel PHYLIP programs
        that are relevant to the study of protein evolution on several protein datasets.
        Conclusions: Calculations that currently take a few days on a state of the
        art desktop workstation are reduced to calculations that can be performed
        over lunchtime on a modern parallel computer. Of the three protein methods
        tested, the maximum likelihood method scales the best, followed by the distance
        method, and then the maximum parsimony method. However, the maximum likelihood
        method requires significant memory resources, which limits its application
        to more moderately sized protein datasets. © 2010 Ropelewski et al.'
      authors:
      - name: Ropelewski A.J.
      - name: Nicholas H.B.
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      citationCount: 13
      date: '2010-12-09T00:00:00Z'
      journal: PLoS ONE
      title: 'MPI-PHYLIP: Parallelizing computationally intensive phylogenetic analysis
        routines for the analysis of large protein families'
    note: null
    pmcid: PMC2981553
    pmid: '21085574'
    type: []
    version: null
  - doi: 10.1385/1-59259-192-2:243
    metadata: null
    note: null
    pmcid: null
    pmid: '10547839'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Phylogenetics
    uri: http://edamontology.org/topic_3293
  - term: Phylogeny
    uri: http://edamontology.org/topic_0084
  - term: Model organisms
    uri: http://edamontology.org/topic_0621
  - term: Gene and protein families
    uri: http://edamontology.org/topic_0623
  - term: Physiology
    uri: http://edamontology.org/topic_3300
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2020-06-05T08:52:25Z'
  biotoolsCURIE: biotools:calibracurve
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  collectionID:
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  - CUBiMed.RUB
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  cost: Free of charge
  credit:
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    fundrefid: null
    gridid: null
    name: PD Dr. Martin Eisenacher
    note: If contacting use "SPARROW" in subject line to avoid mail deluge.
    orcidid: null
    rorid: null
    typeEntity: Person
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    url: null
  - email: null
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    name: de.NBI
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    orcidid: null
    rorid: null
    typeEntity: Project
    typeRole:
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    - Maintainer
    - Support
    url: https://www.denbi.de/
  - email: michael.kohl@rub.de
    fundrefid: null
    gridid: null
    name: Dr. Michael Kohl
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  description: A highly useful and flexible tool for calibration of targeted MS‐based
    measurements. CalibraCurve enables an automated batch-mode determination of dynamic
    linear ranges and quantification limits for both targeted proteomics and similar
    assays. The software uses a variety of measures to assess the accuracy of the
    calibration and provides intuitive visualizations.
  documentation:
  - note: null
    type:
    - Installation instructions
    - Citation instructions
    - General
    - User manual
    - Training material
    - Terms of use
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  download:
  - note: null
    type: Downloads page
    url: https://github.com/mpc-bioinformatics/CalibraCurve
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  function:
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    input:
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    operation:
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  language:
  - R
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  license: BSD-3-Clause
  link:
  - note: null
    type:
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  name: CalibraCurve
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  - Windows
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  otherID: []
  owner: BioInfra.Prot
  publication:
  - doi: 10.1002/pmic.201900143
    metadata:
      abstract: Targeted proteomics techniques allow accurate quantitative measurements
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        of robust protein assays in several sensitive areas, for example, in health
        care. However, exploiting the full method potential requires reliable determination
        of the dynamic range along with related quantification limits for each analyte.
        Here, a software named CalibraCurve that enables an automated batch-mode determination
        of dynamic linear ranges and quantification limits for both targeted proteomics
        and similar assays is presented. The software uses a variety of measures to
        assess the accuracy of the calibration, namely precision and trueness. Two
        different kinds of customizable graphs are created (calibration curves and
        response factor plots). The accuracy measures and the graphs offer an intuitive,
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        Thus, CalibraCurve is deemed a highly useful and flexible tool to facilitate
        the development and control of reliable SRM/MRM-MS-based proteomics assays.
      authors:
      - name: Kohl M.
      - name: Stepath M.
      - name: Bracht T.
      - name: Megger D.A.
      - name: Sitek B.
      - name: Marcus K.
      - name: Eisenacher M.
      citationCount: 4
      date: '2020-06-01T00:00:00Z'
      journal: Proteomics
      title: 'CalibraCurve: A Tool for Calibration of Targeted MS-Based Measurements'
    note: null
    pmcid: null
    pmid: '32086983'
    type:
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  toolType:
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  - Script
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  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
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    uri: http://edamontology.org/topic_3678
  validated: 1
  version:
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  additionDate: '2026-06-04T07:54:19.689100Z'
  biotoolsCURIE: biotools:LongTR
  biotoolsID: LongTR
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  description: Tandem repeat genotyping with long reads, being a modified version
    of HipSTR.
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  function:
  - cmd: null
    input:
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    - data:
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      format:
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        uri: http://edamontology.org/format_2572
    note: null
    operation:
    - term: Genotyping
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    output:
    - data:
        term: Genotype/phenotype report
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      format:
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        uri: http://edamontology.org/format_3016
  homepage: https://github.com/gymrek-lab/LongTR
  homepage_status: 0
  language:
  - Python
  - C++
  - C
  - Shell
  lastUpdate: '2026-06-04T07:54:19.694217Z'
  license: GPL-2.0
  link: []
  maturity: Mature
  name: LongTR
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  - Mac
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  owner: veitveit11
  publication:
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    metadata: null
    note: null
    pmcid: PMC11229021
    pmid: '38965568'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Comparative genomics
    uri: http://edamontology.org/topic_0797
  - term: Mapping
    uri: http://edamontology.org/topic_0102
  - term: Long-read sequencing
    uri: http://edamontology.org/topic_4056
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  version:
  - v1.2
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  additionDate: '2026-06-03T08:48:08.426169Z'
  biotoolsCURIE: biotools:mpa-cloud
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  confidence_flag: null
  cost: Free of charge
  credit:
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    fundrefid: null
    gridid: null
    name: Kay Schallert
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: null
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    name: Daniel Kautzner
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    url: null
  - email: null
    fundrefid: null
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    name: Benjamin J. Saalfeld
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  - email: null
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    name: Prof. Dr.-Ing. Robert Heyer
    note: null
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    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Ludwig Knoche
    note: null
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    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Malte Böttcher
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  description: The MetaProteomeAnalyzer Cloud (MPA Cloud) is an intuitive, open-source
    tool for metaproteomics data analysis and interpretation, designed to analyse
    comprehensive metaproteomics data from tandem mass spectrometry experiments through
    a web interface.
  documentation:
  - note: null
    type:
    - User manual
    url: https://mdoa-tools.bi.denbi.de/mpacloud/documentation
  download: []
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  language:
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  - TypeScript
  lastUpdate: '2026-06-03T11:12:01.769057Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
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    type:
    - Repository
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  name: MetaProteomeAnalyzer-Cloud
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  owner: benjamin4
  publication:
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    metadata: null
    note: null
    pmcid: null
    pmid: '32859984'
    type: []
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  - doi: 10.3389/fmicb.2019.01883
    metadata: null
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  - doi: 10.1021/acs.analchem.7b03544
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    note: null
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    version: null
  - doi: 10.1021/pr501246w
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    note: null
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    pmid: '25660940'
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    version: null
  relation:
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    type: isNewVersionOf
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    type: isNewVersionOf
  toolType:
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  topic:
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    uri: http://edamontology.org/topic_0078
  - term: Metaproteomics
    uri: http://edamontology.org/topic_4060
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  validated: 0
  version: []
- accessibility: Open access (with restrictions)
  additionDate: '2025-05-29T09:19:51.404419Z'
  biotoolsCURIE: biotools:mr-based_dipg_tumour_detection_and_segmentation
  biotoolsID: mr-based_dipg_tumour_detection_and_segmentation
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  cost: Free of charge (with restrictions)
  credit:
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    fundrefid: null
    gridid: null
    name: GIBI230 - HULAFE
    note: null
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    rorid: null
    typeEntity: Institute
    typeRole:
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    url: null
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    fundrefid: null
    gridid: null
    name: Matias Fernandez-Paton
    note: null
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    typeEntity: Person
    typeRole:
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    url: null
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    name: Pedro-Miguel Martinez-Girones
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    typeEntity: Person
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    url: null
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    name: Adrian Galiana-Bordera
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    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
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    name: Carina Soler-Pons
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    typeEntity: Person
    typeRole:
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    - Support
    url: null
  - email: leonor_cerda@iislafe.es
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  - email: luis_marti@iislafe.es
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    typeEntity: Person
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  description: The tool performs an automatic segmentation of the possible DIPG tumours
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    workflow from DICOM images to DICOM seg tumoral masks.
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    note: null
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  - cmd: "docker run --rm --gpus all \\\n  -v /path/to/input:/input -v /path/to/output:/output\
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    note: null
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  homepage: https://harbor.eucaim.cancerimage.eu/harbor/projects/4/repositories/mr-based_dipg_tumour_detection_and_segmentation/info-tab
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  description: 'The tool is designed to perform a customisable image pre-processing
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  description: A tool based on artificial intelligence that is able to perform a categorisation
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  operatingSystem:
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  - Linux
  - Mac
  otherID: []
  owner: veitveit11
  publication:
  - doi: 10.1038/s41592-021-01308-y
    metadata: null
    note: null
    pmcid: PMC8916956
    pmid: '34824477'
    type: []
    version: null
  relation: []
  toolType:
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    uri: http://edamontology.org/topic_3383
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  version:
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- accessibility: Open access
  additionDate: '2026-05-20T00:15:17.437872Z'
  biotoolsCURIE: biotools:compucell3d
  biotoolsID: compucell3d
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit: []
  description: CompuCell3D is a multiscale multicellular virtual tissue modeling and
    simulation environment. CompuCell3D is written in C++ and provides Python bindings
    for model and simulation development in Python.
  documentation:
  - note: null
    type:
    - API documentation
    url: https://compucell3d.org/
  - note: null
    type:
    - Training material
    url: https://compucell3d.org/Tutorials
  - note: null
    type:
    - Citation instructions
    url: https://compucell3d.org/Publications
  download: []
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  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Modelling and simulation
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    output: []
  homepage: https://compucell3d.org/SrcBin
  homepage_status: 0
  language:
  - Python
  - C++
  lastUpdate: '2026-05-20T00:31:43.306086Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://compucell3d.org/SrcBin
  - note: null
    type:
    - Discussion forum
    url: https://www.reddit.com/r/CompuCell3D/
  maturity: Mature
  name: CompuCell3D
  operatingSystem:
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  - Linux
  - Mac
  otherID: []
  owner: VKasalica
  publication:
  - doi: 10.1016/b978-0-12-388403-9.00013-8
    metadata: null
    note: null
    pmcid: PMC3612985
    pmid: '22482955'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Systems biology
    uri: http://edamontology.org/topic_2259
  - term: Computational biology
    uri: http://edamontology.org/topic_3307
  validated: 0
  version:
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- accessibility: null
  additionDate: '2026-05-19T13:59:31.461953Z'
  biotoolsCURIE: biotools:evobind
  biotoolsID: evobind
  collectionID: []
  confidence_flag: tool
  cost: null
  credit:
  - email: patrick.bryant@scilifelab.se
    fundrefid: null
    gridid: null
    name: Patrick Bryant
    note: null
    orcidid: https://orcid.org/0000-0003-3439-1866
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: Design of linear and cyclic peptide binders from protein sequence information.
  documentation: []
  download: []
  editPermission:
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    type: private
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  function:
  - cmd: null
    input: []
    note: null
    operation:
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      uri: http://edamontology.org/operation_3080
    - term: Protein design
      uri: http://edamontology.org/operation_4008
    output: []
  homepage: https://github.com/patrickbryant1/EvoBind
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2026-05-19T13:59:31.464940Z'
  license: null
  link:
  - note: null
    type:
    - Other
    url: https://colab.research.google.com/github/patrickbryant1/EvoBind/blob/master/EvoBind.ipynb
  maturity: null
  name: EvoBind
  operatingSystem: []
  otherID: []
  owner: anitamnd
  publication:
  - doi: 10.1038/S42004-025-01601-3
    metadata: null
    note: null
    pmcid: PMC12280060
    pmid: '40691301'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Protein folding, stability and design
    uri: http://edamontology.org/topic_0130
  - term: Structure prediction
    uri: http://edamontology.org/topic_0082
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2026-05-19T08:03:00.359212Z'
  biotoolsCURIE: biotools:circlator
  biotoolsID: circlator
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: mh12@sanger.ac.uk
    fundrefid: null
    gridid: null
    name: Martin Hunt
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: Circlator is a tool to circularize genome assemblies. It will attempt
    to identify each circular sequence and output a linearised version of it. It does
    this by assembling all reads that map to contig ends and comparing the resulting
    contigs with the input assembly.
  documentation: []
  download: []
  editPermission:
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  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Genome assembly
      uri: http://edamontology.org/operation_0525
    - term: Mapping assembly
      uri: http://edamontology.org/operation_0523
    output: []
  homepage: https://sanger-pathogens.github.io/circlator/
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2026-05-19T08:04:05.768954Z'
  license: GD
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/sanger-pathogens/circlator
  maturity: Mature
  name: Circlator
  operatingSystem: []
  otherID: []
  owner: anitamnd
  publication:
  - doi: 10.1186/S13059-015-0849-0
    metadata: null
    note: null
    pmcid: PMC4699355
    pmid: '26714481'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  validated: 0
  version: []
- accessibility: null
  additionDate: '2025-05-15T11:35:23.428773Z'
  biotoolsCURIE: biotools:plantismash
  biotoolsID: plantismash
  collectionID: []
  confidence_flag: null
  cost: null
  credit: []
  description: PlantiSMASH is a specialized extension of antiSMASH for the identification
    and analysis of biosynthetic gene clusters (BGCs) in plant genomes. It supports
    advanced plant-specific detection rules and features for comparative genomics,
    visualization, and more.
  documentation:
  - note: null
    type:
    - General
    url: https://plantismash.github.io/documentation/
  download:
  - note: null
    type: Software package
    url: https://github.com/plantismash/plantismash/releases
    version: 2.0-beta4
  editPermission:
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  function: []
  homepage: https://plantismash.bioinformatics.nl/
  homepage_status: 0
  language: []
  lastUpdate: '2026-05-15T12:25:33.148463Z'
  license: AGPL-3.0
  link: []
  maturity: null
  name: plantiSMASH
  operatingSystem:
  - Mac
  - Windows
  - Linux
  otherID: []
  owner: elena0
  publication:
  - doi: 10.1093/nar/gkx305
    metadata: null
    note: null
    pmcid: PMC5570173
    pmid: null
    type: []
    version: '1.0'
  - doi: 10.1016/j.jmb.2026.169798
    metadata: null
    note: 'plantiSMASH 2.0: Improvements to Detection, Annotation, and Prioritization
      of Plant Biosynthetic Gene Clusters'
    pmcid: null
    pmid: '41962628'
    type:
    - Primary
    version: '2.0'
  relation: []
  toolType: []
  topic:
  - term: Transcription factors and regulatory sites
    uri: http://edamontology.org/topic_0749
  - term: Data mining
    uri: http://edamontology.org/topic_3473
  - term: Functional genomics
    uri: http://edamontology.org/topic_0085
  validated: 0
  version:
  - 2.0-beta4
- accessibility: Open access
  additionDate: '2026-05-13T05:45:59.510938Z'
  biotoolsCURIE: biotools:framexplore
  biotoolsID: framexplore
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: vidhuvijay2003@gmail.com
    fundrefid: null
    gridid: null
    name: Vidhu S Vijay
    note: MS Bioinformatics student at Amrita Vishwa Vidyapeetham; creator and maintainer
      of FrameXplore.
    orcidid: https://orcid.org/0009-0009-1182-2089
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    - Maintainer
    url: https://github.com/Vidhusv
  description: FrameXplore is a Google Colab notebook that extends ColabFold to automatically
    identify and correct disulfide bonds in cysteine‑rich protein structures. After
    a standard ColabFold prediction, it extracts all cysteine residues, computes Cα–Cα
    and S–S distances, identifies true disulfide bonds using geometric cutoffs (Cα–Cα
    < 6.5 Å, S–S < 2.5 Å), writes a corrected PDB with proper CONECT records, and
    provides an interactive 3D view.
  documentation:
  - note: Quick start guide, example test case, methodology explanation, citation,
      and repository contents
    type:
    - General
    url: https://github.com/Vidhusv/FRAMEXPLORER/blob/main/README.md
  download:
  - note: Latest version of the complete repository as a ZIP file
    type: Source code
    url: https://github.com/Vidhusv/FRAMEXPLORER/archive/refs/heads/main.zip
    version: 1.0.0
  - note: Direct download of the Colab notebook (.ipynb file). Can be run locally
      or uploaded to Google Colab.
    type: Binaries
    url: https://raw.githubusercontent.com/Vidhusv/FRAMEXPLORER/main/FrameXplore.ipynb
    version: 1.0.0
  editPermission:
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    type: public
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  elixirNode: []
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  elixir_badge: 0
  function: []
  homepage: https://github.com/Vidhusv/FRAMEXPLORER
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2026-05-13T06:23:55.557041Z'
  license: MIT
  link:
  - note: GitHub repository with source code, documentation, and logo
    type:
    - Repository
    url: https://github.com/Vidhusv/FRAMEXPLORER
  - note: Report bugs, suggest features, or ask questions
    type:
    - Issue tracker
    url: https://github.com/Vidhusv/FRAMEXPLORER/issues
  maturity: Emerging
  name: FrameXplore
  operatingSystem:
  - Linux
  - Mac
  - Windows
  otherID:
  - type: doi
    value: doi:10.5281/zenodo.20135079
    version: null
  owner: vidhu
  publication:
  - doi: 10.1038/s41592-022-01488-1
    metadata: null
    note: 'ColabFold: making protein folding accessible to all. Nature Methods, 2022.'
    pmcid: PMC9184281
    pmid: '35637307'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Biosciences
    uri: http://edamontology.org/topic_4019
  validated: 0
  version:
  - 1.0.0
- accessibility: null
  additionDate: '2026-05-06T23:40:03.794540Z'
  biotoolsCURIE: biotools:generode
  biotoolsID: generode
  collectionID: []
  confidence_flag: null
  cost: null
  credit: []
  description: Workflow for whole genome sequencing analysis, including patterns of
    genome erosion. Written in Snakemake workflow language.
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/NBISweden/GenErode
  - note: null
    type:
    - User manual
    url: https://github.com/NBISweden/GenErode/wiki
  download: []
  editPermission:
    authors: []
    type: public
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  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: DNA sequence
        uri: http://edamontology.org/data_3494
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: null
    operation:
    - term: Sequence masking
      uri: http://edamontology.org/operation_0368
    - term: Genome indexing
      uri: http://edamontology.org/operation_3211
    output:
    - data:
        term: DNA sequence
        uri: http://edamontology.org/data_3494
      format:
      - term: BED
        uri: http://edamontology.org/format_3003
  - cmd: null
    input:
    - data:
        term: DNA sequence
        uri: http://edamontology.org/data_3494
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
    note: null
    operation:
    - term: Read mapping
      uri: http://edamontology.org/operation_3198
    - term: Sequence trimming
      uri: http://edamontology.org/operation_3192
    - term: Nucleic acid sequence analysis
      uri: http://edamontology.org/operation_2478
    output:
    - data:
        term: DNA sequence
        uri: http://edamontology.org/data_3494
      format:
      - term: BAM
        uri: http://edamontology.org/format_2572
  - cmd: null
    input:
    - data:
        term: DNA sequence
        uri: http://edamontology.org/data_3494
      format:
      - term: BAM
        uri: http://edamontology.org/format_2572
    note: null
    operation:
    - term: Sequencing quality control
      uri: http://edamontology.org/operation_3218
    - term: Variant calling
      uri: http://edamontology.org/operation_3227
    - term: Genotyping
      uri: http://edamontology.org/operation_3196
    output:
    - data:
        term: Sequence variations
        uri: http://edamontology.org/data_3498
      format:
      - term: VCF
        uri: http://edamontology.org/format_3016
  homepage: https://github.com/NBISweden/GenErode
  homepage_status: 0
  language:
  - Other
  lastUpdate: '2026-05-06T23:40:03.797298Z'
  license: GPL-3.0
  link: []
  maturity: Mature
  name: GenErode
  operatingSystem: []
  otherID: []
  owner: johangustafsson
  publication:
  - doi: 10.1186/s12859-022-04757-0
    metadata: null
    note: null
    pmcid: PMC9195343
    pmid: '35698034'
    type:
    - Method
    version: null
  relation: []
  toolType:
  - Workflow
  topic:
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  validated: 0
  version: []
- accessibility: null
  additionDate: '2022-07-04T14:39:20.644374Z'
  biotoolsCURIE: biotools:hifiasm
  biotoolsID: hifiasm
  collectionID: []
  confidence_flag: null
  cost: null
  credit: []
  description: 'Hifiasm: a haplotype-resolved assembler for accurate Hifi reads'
  documentation:
  - note: null
    type:
    - General
    url: https://hifiasm.readthedocs.io/en/latest/
  download: []
  editPermission:
    authors:
    - bebatut
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Genome assembly
      uri: http://edamontology.org/operation_0525
    - term: De-novo assembly
      uri: http://edamontology.org/operation_0524
    output: []
  homepage: https://github.com/chhylp123/hifiasm
  homepage_status: 0
  language:
  - C
  - C++
  lastUpdate: '2026-05-05T08:11:43.608451Z'
  license: MIT
  link: []
  maturity: null
  name: Hifiasm
  operatingSystem: []
  otherID: []
  owner: alexcorm
  publication:
  - doi: 10.1038/s41592-020-01056-5
    metadata:
      abstract: Haplotype-resolved de novo assembly is the ultimate solution to the
        study of sequence variations in a genome. However, existing algorithms either
        collapse heterozygous alleles into one consensus copy or fail to cleanly separate
        the haplotypes to produce high-quality phased assemblies. Here we describe
        hifiasm, a de novo assembler that takes advantage of long high-fidelity sequence
        reads to faithfully represent the haplotype information in a phased assembly
        graph. Unlike other graph-based assemblers that only aim to maintain the contiguity
        of one haplotype, hifiasm strives to preserve the contiguity of all haplotypes.
        This feature enables the development of a graph trio binning algorithm that
        greatly advances over standard trio binning. On three human and five nonhuman
        datasets, including California redwood with a ~30-Gb hexaploid genome, we
        show that hifiasm frequently delivers better assemblies than existing tools
        and consistently outperforms others on haplotype-resolved assembly.
      authors:
      - name: Cheng H.
      - name: Concepcion G.T.
      - name: Feng X.
      - name: Zhang H.
      - name: Li H.
      citationCount: 1739
      date: '2021-02-01T00:00:00Z'
      journal: Nature Methods
      title: Haplotype-resolved de novo assembly using phased assembly graphs with
        hifiasm
    note: null
    pmcid: PMC7961889
    pmid: '33526886'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  validated: 0
  version:
  - 0.16.1
- accessibility: null
  additionDate: '2026-05-05T04:14:58.521066Z'
  biotoolsCURIE: biotools:chai-1
  biotoolsID: chai-1
  collectionID: []
  confidence_flag: null
  cost: null
  credit: []
  description: Structure prediction of DNA, RNA, proteins, and small molecules using
    a multi-modal foundation model.
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/chaidiscovery/chai-lab/blob/main/README.md
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: DNA structure prediction
      uri: http://edamontology.org/operation_2442
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Ab initio structure prediction
      uri: http://edamontology.org/operation_0476
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: RNA structure prediction
      uri: http://edamontology.org/operation_2441
    output: []
  homepage: https://github.com/chaidiscovery/chai-lab
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2026-05-05T04:14:58.524996Z'
  license: Apache-2.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/chaidiscovery/chai-lab
  maturity: null
  name: Chai-1
  operatingSystem: []
  otherID: []
  owner: johangustafsson
  publication:
  - doi: 10.1101/2024.10.10.615955
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Preprint
    version: null
  - doi: 10.1101/2025.07.05.663018
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Preprint
    version: null
  - doi: 10.1038/s41592-022-01488-1
    metadata: null
    note: Cite this if automatic MMseqs2 MSA generation is used.
    pmcid: PMC9184281
    pmid: '35637307'
    type:
    - Primary
    version: null
  relation: []
  toolType: []
  topic:
  - term: Structure prediction
    uri: http://edamontology.org/topic_0082
  validated: 0
  version: []
- accessibility: null
  additionDate: '2026-05-01T11:37:56.074227Z'
  biotoolsCURIE: biotools:verkko
  biotoolsID: verkko
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: Verkko is a hybrid genome assembly pipeline for telomere-to-telomere
    assembly of long reads.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Nucleic acid sequence
        uri: http://edamontology.org/data_2977
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
    note: null
    operation:
    - term: Scaffolding
      uri: http://edamontology.org/operation_3216
    - term: Sequence assembly
      uri: http://edamontology.org/operation_0310
    output:
    - data:
        term: Nucleic acid sequence
        uri: http://edamontology.org/data_2977
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Sequence assembly report
        uri: http://edamontology.org/data_3181
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
  homepage: https://github.com/marbl/verkko
  homepage_status: 0
  language:
  - Perl
  - Python
  - Bash
  lastUpdate: '2026-05-01T11:37:56.076538Z'
  license: Freeware
  link: []
  maturity: Mature
  name: Verkko
  operatingSystem:
  - Linux
  otherID: []
  owner: n.m.palmblad@lumc.nl
  publication:
  - doi: 10.1038/s41587-023-01662-6
    metadata: null
    note: null
    pmcid: PMC10427740
    pmid: '36797493'
    type:
    - Primary
    version: null
  - doi: 10.1101/gr.280383.124
    metadata: null
    note: null
    pmcid: PMC12212074
    pmid: '40389285'
    type:
    - Primary
    version: 2.0.0
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  - term: Long-read sequencing
    uri: http://edamontology.org/topic_4056
  validated: 0
  version:
  - 2.3.2
- accessibility: Open access
  additionDate: '2026-05-01T10:14:13.412969Z'
  biotoolsCURIE: biotools:scandan-dicom-labelling
  biotoolsID: scandan-dicom-labelling
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: Regular expression used during the SCANDAN project to label MRI scans
    based on DICOM tag.
  documentation:
  - note: null
    type:
    - Quick start guide
    url: https://github.com/SCANDAN-Team/SCANDAN-DICOM-labelling/blob/main/README.md
  download:
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  description: RACLAHE (Region-Adaptive Contrast Limited Adaptive Histogram Equalization)
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  - note: null
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    note: Cite if you use automatic MSA generation.
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  description: The InChI Open Education Resource (OER) provides resources, training
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  - Linux
  otherID: []
  owner: jdianes
  publication:
  - doi: 10.1016/j.softx.2015.06.001
    metadata:
      abstract: GROMACS is one of the most widely used open-source and free software
        codes in chemistry, used primarily for dynamical simulations of biomolecules.
        It provides a rich set of calculation types, preparation and analysis tools.
        Several advanced techniques for free-energy calculations are supported. In
        version 5, it reaches new performance heights, through several new and enhanced
        parallelization algorithms. These work on every level; SIMD registers inside
        cores, multithreading, heterogeneous CPU-GPU acceleration, state-of-the-art
        3D domain decomposition, and ensemble-level parallelization through built-in
        replica exchange and the separate Copernicus framework. The latest best-in-class
        compressed trajectory storage format is supported.
      authors:
      - name: Abraham M.J.
      - name: Murtola T.
      - name: Schulz R.
      - name: Pall S.
      - name: Smith J.C.
      - name: Hess B.
      - name: Lindah E.
      citationCount: 15418
      date: '2015-01-01T00:00:00Z'
      journal: SoftwareX
      title: 'Gromacs: High performance molecular simulations through multi-level
        parallelism from laptops to supercomputers'
    note: null
    pmcid: null
    pmid: null
    type:
    - Benchmarking study
    version: null
  - doi: 10.1002/jcc.20291
    metadata:
      abstract: This article describes the software suite GROMACS (Groningen MAchine
        for Chemical Simulation) that was developed at the University of Groningen,
        The Netherlands, in the early 1990s. The software, written in ANSI C, originates
        from a parallel hardware project, and is well suited for parallelization on
        processor clusters. By careful optimization of neighbor searching and of inner
        loop performance, GROMACS is a very fast program for molecular dynamics simulation.
        It does not have a force field of its own, but is compatible with GROMOS,
        OPLS, AMBER, and ENCAD force fields. In addition, it can handle polarizable
        shell models and flexible constraints. The program is versatile, as force
        routines can be added by the user, tabulated functions can be specified, and
        analyses can be easily customized. Nonequilibrium dynamics and free energy
        determinations are incorporated. Interfaces with popular quantum-chemical
        packages (MOPAC, GAMES-UK, GAUSSIAN) are provided to perform mixed MM/QM simulations.
        The package includes about 100 utility and analysis programs. GROMACS is in
        the public domain and distributed (with source code and documentation) under
        the GNU General Public License. It is maintained by a group of developers
        from the Universities of Groningen, Uppsala, and Stockholm, and the Max Planck
        Institute for Polymer Research in Mainz. Its Web site is http://www.gromacs.org.
        © 2005 Wiley Periodicals, Inc.
      authors:
      - name: Van Der Spoel D.
      - name: Lindahl E.
      - name: Hess B.
      - name: Groenhof G.
      - name: Mark A.E.
      - name: Berendsen H.J.C.
      citationCount: 14137
      date: '2005-12-01T00:00:00Z'
      journal: Journal of Computational Chemistry
      title: 'GROMACS: Fast, flexible, and free'
    note: null
    pmcid: null
    pmid: '16211538'
    type:
    - Benchmarking study
    version: null
  - doi: 10.1063/5.0018516
    metadata:
      abstract: The introduction of accelerator devices such as graphics processing
        units (GPUs) has had profound impact on molecular dynamics simulations and
        has enabled order-of-magnitude performance advances using commodity hardware.
        To fully reap these benefits, it has been necessary to reformulate some of
        the most fundamental algorithms, including the Verlet list, pair searching,
        and cutoffs. Here, we present the heterogeneous parallelization and acceleration
        design of molecular dynamics implemented in the GROMACS codebase over the
        last decade. The setup involves a general cluster-based approach to pair lists
        and non-bonded pair interactions that utilizes both GPU and central processing
        unit (CPU) single instruction, multiple data acceleration efficiently, including
        the ability to load-balance tasks between CPUs and GPUs. The algorithm work
        efficiency is tuned for each type of hardware, and to use accelerators more
        efficiently, we introduce dual pair lists with rolling pruning updates. Combined
        with new direct GPU-GPU communication and GPU integration, this enables excellent
        performance from single GPU simulations through strong scaling across multiple
        GPUs and efficient multi-node parallelization.
      authors:
      - name: Pall S.
      - name: Zhmurov A.
      - name: Bauer P.
      - name: Abraham M.
      - name: Lundborg M.
      - name: Gray A.
      - name: Hess B.
      - name: Lindahl E.
      citationCount: 349
      date: '2020-10-07T00:00:00Z'
      journal: Journal of Chemical Physics
      title: Heterogeneous parallelization and acceleration of molecular dynamics
        simulations in GROMACS
    note: null
    pmcid: null
    pmid: '33032406'
    type:
    - Benchmarking study
    version: null
  - doi: 10.1007/978-3-319-15976-8_1
    metadata:
      abstract: GROMACS is a widely used package for biomolecular simulation, and
        over the last two decades it has evolved from small-scale efficiency to advanced
        heterogeneous acceleration and multi-level parallelism targeting some of the
        largest supercomputers in the world. Here, we describe some of the ways we
        have been able to realize this through the use of parallelization on all levels,
        combined with a constant focus on absolute performance. Release 4.6 of GROMACS
        uses SIMD acceleration on a wide range of architectures, GPU offloading acceleration,
        and both OpenMP and MPI parallelism within and between nodes, respectively.
        The recent work on acceleration made it necessary to revisit the fundamental
        algorithms of molecular simulation, including the concept of neighborsearching,
        and we discuss the present and future challenges we see for exascale simulation
        - in particular a very fine-grained task parallelism. We also discuss the
        software management, code peer review and continuous integration testing required
        for a project of this complexity.
      authors:
      - name: Pall S.
      - name: Abraham M.J.
      - name: Kutzner C.
      - name: Hess B.
      - name: Lindahl E.
      citationCount: 752
      date: '2015-01-01T00:00:00Z'
      journal: Lecture Notes in Computer Science (including subseries Lecture Notes
        in Artificial Intelligence and Lecture Notes in Bioinformatics)
      title: Tackling exascale software challenges in molecular dynamics simulations
        with GROMACS
    note: null
    pmcid: null
    pmid: null
    type:
    - Benchmarking study
    version: null
  - doi: 10.1093/bioinformatics/btt055
    metadata:
      abstract: 'Motivation: Molecular simulation has historically been a low-throughput
        technique, but faster computers and increasing amounts of genomic and structural
        data are changing this by enabling large-scale automated simulation of, for
        instance, many conformers or mutants of biomolecules with or without a range
        of ligands. At the same time, advances in performance and scaling now make
        it possible to model complex biomolecular interaction and function in a manner
        directly testable by experiment. These applications share a need for fast
        and efficient software that can be deployed on massive scale in clusters,
        web servers, distributed computing or cloud resources.Results: Here, we present
        a range of new simulation algorithms and features developed during the past
        4 years, leading up to the GROMACS 4.5 software package. The software now
        automatically handles wide classes of biomolecules, such as proteins, nucleic
        acids and lipids, and comes with all commonly used force fields for these
        molecules built-in. GROMACS supports several implicit solvent models, as well
        as new free-energy algorithms, and the software now uses multithreading for
        efficient parallelization even on low-end systems, including windows-based
        workstations. Together with hand-tuned assembly kernels and state-of-the-art
        parallelization, this provides extremely high performance and cost efficiency
        for high-throughput as well as massively parallel simulations. © 2013 The
        Author. Published by Oxford University Press. All rights reserved.'
      authors:
      - name: Pronk S.
      - name: Pall S.
      - name: Schulz R.
      - name: Larsson P.
      - name: Bjelkmar P.
      - name: Apostolov R.
      - name: Shirts M.R.
      - name: Smith J.C.
      - name: Kasson P.M.
      - name: Van Der Spoel D.
      - name: Hess B.
      - name: Lindahl E.
      citationCount: 5927
      date: '2013-04-01T00:00:00Z'
      journal: Bioinformatics
      title: 'GROMACS 4.5: A high-throughput and highly parallel open source molecular
        simulation toolkit'
    note: null
    pmcid: PMC3605599
    pmid: '23407358'
    type: []
    version: null
  - doi: 10.1021/ct700301q
    metadata:
      abstract: Molecular simulation is an extremely useful, but computationally very
        expensive tool for studies of chemical and biomolecular systems. Here, we
        present a new implementation of our molecular simulation toolkit GROMACS which
        now both achieves extremely high performance on single processors from algorithmic
        optimizations and hand-coded routines and simultaneously scales very well
        on parallel machines. The code encompasses a minimal-communication domain
        decomposition algorithm, full dynamic load balancing, a state-of-the-art parallel
        constraint solver, and efficient virtual site algorithms that allow removal
        of hydrogen atom degrees of freedom to enable integration time steps up to
        5 fs for atomistic simulations also in parallel. To improve the scaling properties
        of the common particle mesh Ewald electrostatics algorithms, we have in addition
        used a Multiple-Program, Multiple-Data approach, with separate node domains
        responsible for direct and reciprocal space interactions. Not only does this
        combination of algorithms enable extremely long simulations of large systems
        but also it provides that simulation performance on quite modest numbers of
        standard cluster nodes. © 2008 American Chemical Society.
      authors:
      - name: Hess B.
      - name: Kutzner C.
      - name: Van Der Spoel D.
      - name: Lindahl E.
      citationCount: 13627
      date: '2008-03-01T00:00:00Z'
      journal: Journal of Chemical Theory and Computation
      title: 'GRGMACS 4: Algorithms for highly efficient, load-balanced, and scalable
        molecular simulation'
    note: null
    pmcid: null
    pmid: '26620784'
    type:
    - Benchmarking study
    version: null
  - doi: 10.1007/s008940100045
    metadata:
      abstract: GROMACS 3.0 is the latest release of a versatile and very well optimized
        package for molecular simulation. Much effort has been devoted to achieving
        extremely high performance on both workstations and parallel computers. The
        design includes an extraction of virial and periodic boundary conditions from
        the loops over pairwise interactions, and special software routines to enable
        rapid calculation of x-1/2. Inner loops are generated automatically in C or
        Fortran at compile time, with optimizations adapted to each architecture.
        Assembly loops using SSE and 3DNow! Multimedia instructions are provided for
        x86 processors, resulting in exceptional performance on inexpensive PC workstations.
        The interface is simple and easy to use (no scripting language), based on
        standard command line arguments with self-explanatory functionality and integrated
        documentation. All binary files are independent of hardware endian and can
        be read by versions of GROMACS compiled using different floating-point precision.
        A large collection of flexible tools for trajectory analysis is included,
        with output in the form of finished Xmgr/Grace graphs. A basic trajectory
        viewer is included, and several external visualization tools can read the
        GROMACS trajectory format.
      authors:
      - name: Lindahl E.
      - name: Hess B.
      - name: van der Spoel D.
      citationCount: 6227
      date: '2001-12-01T00:00:00Z'
      journal: Journal of Molecular Modeling
      title: 'GROMACS 3.0: A package for molecular simulation and trajectory analysis'
    note: null
    pmcid: null
    pmid: null
    type:
    - Benchmarking study
    version: null
  - doi: 10.1016/0010-4655(95)00042-E
    metadata:
      abstract: 'A parallel message-passing implementation of a molecular dynamics
        (MD) program that is useful for bio(macro)molecules in aqueous environment
        is described. The software has been developed for a custom-designed 32-processor
        ring GROMACS (GROningen MAchine for Chemical Simulation) with communication
        to and from left and right neighbours, but can run on any parallel system
        onto which a a ring of processors can be mapped and which supports PVM-like
        block send and receive calls. The GROMACS software consists of a preprocessor,
        a parallel MD and energy minimization program that can use an arbitrary number
        of processors (including one), an optional monitor, and several analysis tools.
        The programs are written in ANSI C and available by ftp (information: gromacs@chem.rug.nl).
        The functionality is based on the GROMOS (GROningen MOlecular Simulation)
        package (van Gunsteren and Berendsen, 1987; BIOMOS B.V., Nijenborgh 4, 9747
        AG Groningen). Conversion programs between GROMOS and GROMACS formats are
        included. The MD program can handle rectangular periodic boundary conditions
        with temperature and pressure scaling. The interactions that can be handled
        without modification are variable non-bonded pair interactions with Coulomb
        and Lennard-Jones or Buckingham potentials, using a twin-range cut-off based
        on charge groups, and fixed bonded interactions of either harmonic or constraint
        type for bonds and bond angles and either periodic or cosine power series
        interactions for dihedral angles. Special forces can be added to groups of
        particles (for non-equilibrium dynamics or for position restraining) or between
        particles (for distance restraints). The parallelism is based on particle
        decomposition. Interprocessor communication is largely limited to position
        and force distribution over the ring once per time step. © 1995.'
      authors:
      - name: Berendsen H.J.C.
      - name: van der Spoel D.
      - name: van Drunen R.
      citationCount: 8425
      date: '1995-09-02T00:00:00Z'
      journal: Computer Physics Communications
      title: 'GROMACS: A message-passing parallel molecular dynamics implementation'
    note: null
    pmcid: null
    pmid: null
    type:
    - Benchmarking study
    version: null
  - doi: 10.1002/jcc.24030
    metadata:
      abstract: The molecular dynamics simulation package GROMACS runs efficiently
        on a wide variety of hardware from commodity workstations to high performance
        computing clusters. Hardware features are well-exploited with a combination
        of single instruction multiple data, multithreading, and message passing interface
        (MPI)-based single program multiple data/multiple program multiple data parallelism
        while graphics processing units (GPUs) can be used as accelerators to compute
        interactions off-loaded from the CPU. Here, we evaluate which hardware produces
        trajectories with GROMACS 4.6 or 5.0 in the most economical way. We have assembled
        and benchmarked compute nodes with various CPU/GPU combinations to identify
        optimal compositions in terms of raw trajectory production rate, performance-to-price
        ratio, energy efficiency, and several other criteria. Although hardware prices
        are naturally subject to trends and fluctuations, general tendencies are clearly
        visible. Adding any type of GPU significantly boosts a node's simulation performance.
        For inexpensive consumer-class GPUs this improvement equally reflects in the
        performance-to-price ratio. Although memory issues in consumer-class GPUs
        could pass unnoticed as these cards do not support error checking and correction
        memory, unreliable GPUs can be sorted out with memory checking tools. Apart
        from the obvious determinants for cost-efficiency like hardware expenses and
        raw performance, the energy consumption of a node is a major cost factor.
        Over the typical hardware lifetime until replacement of a few years, the costs
        for electrical power and cooling can become larger than the costs of the hardware
        itself. Taking that into account, nodes with a well-balanced ratio of CPU
        and consumer-class GPU resources produce the maximum amount of GROMACS trajectory
        over their lifetime.
      authors:
      - name: Kutzner C.
      - name: Pall S.
      - name: Fechner M.
      - name: Esztermann A.
      - name: De Groot B.L.
      - name: Grubmuller H.
      citationCount: 198
      date: '2015-10-01T00:00:00Z'
      journal: Journal of Computational Chemistry
      title: 'Best bang for your buck: GPU nodes for GROMACS biomolecular simulations'
    note: null
    pmcid: PMC5042102
    pmid: '26238484'
    type:
    - Benchmarking study
    version: null
  - doi: 10.1002/jcc.26011
    metadata:
      abstract: We identify hardware that is optimal to produce molecular dynamics
        (MD) trajectories on Linux compute clusters with the GROMACS 2018 simulation
        package. Therefore, we benchmark the GROMACS performance on a diverse set
        of compute nodes and relate it to the costs of the nodes, which may include
        their lifetime costs for energy and cooling. In agreement with our earlier
        investigation using GROMACS 4.6 on hardware of 2014, the performance to price
        ratio of consumer GPU nodes is considerably higher than that of CPU nodes.
        However, with GROMACS 2018, the optimal CPU to GPU processing power balance
        has shifted even more toward the GPU. Hence, nodes optimized for GROMACS 2018
        and later versions enable a significantly higher performance to price ratio
        than nodes optimized for older GROMACS versions. Moreover, the shift toward
        GPU processing allows to cheaply upgrade old nodes with recent GPUs, yielding
        essentially the same performance as comparable brand-new hardware. © 2019
        Wiley Periodicals, Inc.
      authors:
      - name: Kutzner C.
      - name: Pall S.
      - name: Fechner M.
      - name: Esztermann A.
      - name: de Groot B.L.
      - name: Grubmuller H.
      citationCount: 288
      date: '2019-10-15T00:00:00Z'
      journal: Journal of Computational Chemistry
      title: 'More bang for your buck: Improved use of GPU nodes for GROMACS 2018'
    note: null
    pmcid: null
    pmid: '31260119'
    type:
    - Benchmarking study
    version: null
  relation: []
  toolType:
  - Command-line tool
  - Library
  - Suite
  topic:
  - term: Molecular dynamics
    uri: http://edamontology.org/topic_0176
  validated: 1
  version: []
- accessibility: null
  additionDate: '2026-03-27T11:23:52.385389Z'
  biotoolsCURIE: biotools:hicap
  biotoolsID: hicap
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  description: Identify cap locus serotype and structure in your Haemophilus influenzae
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  owner: bgruening
  publication:
  - doi: 10.1128/jcm.00190-19
    metadata: null
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    pmcid: PMC6535587
    pmid: '30944197'
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- accessibility: Open access
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    url: https://biotools.readthedocs.io/en/latest/contributors.html
  description: The community registry of computational tools and data resources for
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    url: https://biotools.readthedocs.io/en/latest/api_usage_guide.html
  - note: API Reference
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    url: https://biotools.readthedocs.io/en/latest/api_reference.html
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    type:
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    url: https://biotools.readthedocs.io/en/latest/curators_guide.html
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    metadata: null
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  toolType:
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  topic:
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  - term: Data curation and archival
    uri: http://edamontology.org/topic_0219
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    uri: http://edamontology.org/topic_3307
  validated: 1
  version: []
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