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  description: MirGeneDB is a database of manually curated microRNA genes that have
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    et al. 2020 and Fromm et al 2022. MirGeneDB 3.0 (Clarke and Hoye et al. 2024 )
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    families from 114 metazoan species. All microRNAs can be browsed, searched and
    downloaded.
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  - doi: 10.1093/nar/gkab1101
    metadata:
      abstract: We describe an update of MirGeneDB, the manually curated microRNA
        gene database. Adhering to uniform and consistent criteria for microRNA annotation
        and nomenclature, we substantially expanded MirGeneDB with 30 additional species
        representing previously missing metazoan phyla such as sponges, jellyfish,
        rotifers and flatworms. MirGeneDB 2.1 now consists of 75 species spanning
        over ∼800 million years of animal evolution, and contains a total number of
        16 670 microRNAs from 1549 families. Over 6000 microRNAs were added in this
        update using ∼550 datasets with ∼7.5 billion sequencing reads. By adding new
        phylogenetically important species, especially those relevant for the study
        of whole genome duplication events, and through updating evolutionary nodes
        of origin for many families and genes, we were able to substantially refine
        our nomenclature system. All changes are traceable in the specifically developed
        MirGeneDB version tracker. The performance of read-pages is improved and microRNA
        expression matrices for all tissues and species are now also downloadable.
        Altogether, this update represents a significant step toward a complete sampling
        of all major metazoan phyla, and a widely needed foundation for comparative
        microRNA genomics and transcriptomics studies. MirGeneDB 2.1 is part of RNAcentral
        and Elixir Norway, publicly and freely available at http://www.mirgenedb.org/.
      authors:
      - name: Fromm B.
      - name: Hoye E.
      - name: Domanska D.
      - name: Zhong X.
      - name: Aparicio-Puerta E.
      - name: Ovchinnikov V.
      - name: Umu S.U.
      - name: Chabot P.J.
      - name: Kang W.
      - name: Aslanzadeh M.
      - name: Tarbier M.
      - name: Marmol-Sanchez E.
      - name: Urgese G.
      - name: Johansen M.
      - name: Hovig E.
      - name: Hackenberg M.
      - name: Friedlander M.R.
      - name: Peterson K.J.
      citationCount: 95
      date: '2022-01-07T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'MirGeneDB 2.1: Toward a complete sampling of all major animal phyla'
    note: null
    pmcid: PMC8728216
    pmid: '34850127'
    type:
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    version: '2.1'
  - doi: 10.1093/nar/gkz885
    metadata:
      abstract: Small non-coding RNAs have gained substantial attention due to their
        roles in animal development and human disorders. Among them, microRNAs are
        special because individual gene sequences are conserved across the animal
        kingdom. In addition, unique and mechanistically well understood features
        can clearly distinguish bona fide miRNAs from the myriad other small RNAs
        generated by cells. However, making this distinction is not a common practice
        and, thus, not surprisingly, the heterogeneous quality of available miRNA
        complements has become a major concern in microRNA research. We addressed
        this by extensively expanding our curated microRNA gene database-MirGeneDB-to
        45 organisms, encompassing a wide phylogenetic swath of animal evolution.
        By consistently annotating and naming 10,899 microRNA genes in these organisms,
        we show that previous microRNA annotations contained not only many false positives,
        but surprisingly lacked >2000 bona fide microRNAs. Indeed, curated microRNA
        complements of closely related organisms are very similar and can be used
        to reconstruct ancestral miRNA repertoires. MirGeneDB represents a robust
        platform for microRNA-based research, providing deeper and more significant
        insights into the biology and evolution of miRNAs as well as biomedical and
        biomarker research. MirGeneDB is publicly and freely available at http://mirgenedb.org/.
      authors:
      - name: Fromm B.
      - name: Domanska D.
      - name: Hoye E.
      - name: Ovchinnikov V.
      - name: Kang W.
      - name: Aparicio-Puerta E.
      - name: Johansen M.
      - name: Flatmark K.
      - name: Mathelier A.
      - name: Hovig E.
      - name: Hackenberg M.
      - name: Friedlander M.R.
      - name: Peterson K.J.
      citationCount: 178
      date: '2020-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'MirGeneDB 2.0: The metazoan microRNA complement'
    note: null
    pmcid: PMC6943042
    pmid: '31598695'
    type:
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    version: '2.0'
  - doi: 10.1146/annurev-genet-120213-092023
    metadata:
      abstract: Although microRNAs (miRNAs) are among the most intensively studied
        molecules of the past 20 years, determining what is and what is not a miRNA
        has not been straightforward. Here, we present a uniform system for the annotation
        and nomenclature of miRNA genes. We show that less than a third of the 1,881
        human miRBase entries, and only approximately 16% of the 7,095 metazoan miRBase
        entries, are robustly supported as miRNA genes. Furthermore, we show that
        the human repertoire of miRNAs has been shaped by periods of intense miRNA
        innovation and that mature gene products show a very different tempo and mode
        of sequence evolution than star products. We establish a new open access database-MirGeneDB
        (http://mirgenedb.org)-to catalog this set of miRNAs, which complements the
        efforts of miRBase but differs from it by annotating the mature versus star
        products and by imposing an evolutionary hierarchy upon this curated and consistently
        named repertoire.
      authors:
      - name: Fromm B.
      - name: Billipp T.
      - name: Peck L.E.
      - name: Johansen M.
      - name: Tarver J.E.
      - name: King B.L.
      - name: Newcomb J.M.
      - name: Sempere L.F.
      - name: Flatmark K.
      - name: Hovig E.
      - name: Peterson K.J.
      citationCount: 435
      date: '2015-11-23T00:00:00Z'
      journal: Annual Review of Genetics
      title: A Uniform System for the Annotation of Vertebrate microRNA Genes and
        the Evolution of the Human microRNAome
    note: null
    pmcid: PMC4743252
    pmid: '26473382'
    type:
    - Primary
    version: '1.0'
  - doi: 10.1093/nar/gkae1094
    metadata:
      abstract: We present a major update of MirGeneDB (3.0), the manually curated
        animal microRNA gene database. Beyond moving to a new server and the creation
        of a computational mirror, we have expanded the database with the addition
        of 33 invertebrate species, including representatives of 5 previously unsampled
        phyla, and 6 mammal species. MirGeneDB now contains entries for 21 822 microRNA
        genes (5160 of these from the new species) belonging to 1743 microRNA families.
        The inclusion of these new species allowed us to refine both the evolutionary
        node of appearance of a number of microRNA genes/families, as well as MirGeneDB's
        phylogenetically informed nomenclature system. Updated covariance models of
        all microRNA families, along with all smallRNA read data are now downloadable.
        These enhanced annotations will allow researchers to analyze microRNA properties
        such as secondary structure and features of their biogenesis within a robust
        phylogenetic context and without the database plagued with numerous false
        positives and false negatives. In light of these improvements, MirGeneDB 3.0
        will assume the responsibility for naming conserved novel metazoan microRNAs.
        MirGeneDB is part of RNAcentral and Elixir Norway and is publicly and freely
        available at mirgenedb.org.
      authors:
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      - name: Hoye E.
      - name: Hembrom A.A.
      - name: Paynter V.M.
      - name: Vinther J.
      - name: Wyrozemski L.
      - name: Biryukova I.
      - name: Formaggioni A.
      - name: Ovchinnikov V.
      - name: Herlyn H.
      - name: Pierce A.
      - name: Wu C.
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      - name: Cheneby J.
      - name: Martinez P.
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      - name: Hovig E.
      - name: Hackenberg M.
      - name: Umu S.U.
      - name: Johansen M.
      - name: Peterson K.J.
      - name: Fromm B.
      citationCount: 6
      date: '2025-01-06T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'MirGeneDB 3.0: Improved taxonomic sampling, uniform nomenclature of
        novel conserved microRNA families and updated covariance models'
    note: null
    pmcid: PMC11701709
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  language: []
  lastUpdate: '2025-07-02T06:56:17.543937Z'
  license: OGTSL
  link:
  - note: Link to data request form.
    type:
    - Service
    url: https://ukbms.org/request-data
  - note: Summary statistics.
    type:
    - Other
    url: https://ukbms.org/official-statistics
  maturity: Mature
  name: UK Butterfly Monitoring Scheme
  operatingSystem: []
  otherID: []
  owner: Keiler_Collier
  publication: []
  relation: []
  toolType:
  - Database portal
  topic:
  - term: Biodiversity
    uri: http://edamontology.org/topic_3050
  - term: Ecology
    uri: http://edamontology.org/topic_0610
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2025-06-18T09:20:19.874306Z'
  biotoolsCURIE: biotools:chopper
  biotoolsID: chopper
  collectionID:
  - ONTeater
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: decosterwouter@gmail.com
    fundrefid: null
    gridid: null
    name: Wouter de Coster
    note: null
    orcidid: https://orcid.org/0000-0002-5248-8197
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: https://gigabaseorgigabyte.wordpress.com
  description: Rust implementation of NanoFilt+NanoLyse, both originally written in
    Python. This tool, intended for long read sequencing such as PacBio or ONT, filters
    and trims a fastq file.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: 'gunzip -c reads.fastq.gz | chopper -q 10 -l 500 | gzip > filtered_reads.fastq.gz

      chopper -q 10 -l 500 -i reads.fastq > filtered_reads.fastq

      chopper -q 10 -l 500 -i reads.fastq.gz | gzip > filtered_reads.fastq.gz'
    input:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
    note: null
    operation:
    - term: Data filtering
      uri: http://edamontology.org/operation_3695
    - term: Sequence trimming
      uri: http://edamontology.org/operation_3192
    output:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
  - cmd: null
    input:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
    note: null
    operation:
    - term: Scatter plot plotting
      uri: http://edamontology.org/operation_2940
    - term: Box-Whisker plot plotting
      uri: http://edamontology.org/operation_2943
    output:
    - data:
        term: Plot
        uri: http://edamontology.org/data_2884
      format:
      - term: JPG
        uri: http://edamontology.org/format_3579
  homepage: https://github.com/wdecoster/chopper
  homepage_status: 0
  language: []
  lastUpdate: '2025-06-30T15:46:01.095401Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/wdecoster/chopper
  maturity: Mature
  name: Chopper
  operatingSystem:
  - Mac
  - Linux
  otherID: []
  owner: Keiler_Collier
  publication:
  - doi: 10.1093/bioinformatics/btad311
    metadata:
      abstract: 'Increases in the cohort size in long-read sequencing projects necessitate
        more efficient software for quality assessment and processing of sequencing
        data from Oxford Nanopore Technologies and Pacific Biosciences. Here, we describe
        novel tools for summarizing experiments, filtering datasets, visualizing phased
        alignments results, and updates to the NanoPack software suite. Availability
        and implementation: The cramino, chopper, kyber, and phasius tools are written
        in Rust and available as executable binaries without requiring installation
        or managing dependencies. Binaries build on musl are available for broad compatibility.
        NanoPlot and NanoComp are written in Python3. Links to the separate tools
        and their documentation can be found at https://github.com/wdecoster/nanopack.
        All tools are compatible with Linux, Mac OS, and the MS Windows Subsystem
        for Linux and are released under the MIT license. The repositories include
        test data, and the tools are continuously tested using GitHub Actions and
        can be installed with the conda dependency manager.'
      authors:
      - name: De Coster W.
      - name: Rademakers R.
      citationCount: 211
      date: '2023-05-01T00:00:00Z'
      journal: Bioinformatics
      title: 'NanoPack2: population-scale evaluation of long-read sequencing data'
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  relation:
  - biotoolsID: nanopack
    type: isNewVersionOf
  toolType:
  - Command-line tool
  topic:
  - term: Sequencing
    uri: http://edamontology.org/topic_3168
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  validated: 0
  version:
  - v0.10.0b
- accessibility: Open access
  additionDate: '2019-11-14T18:08:10Z'
  biotoolsCURIE: biotools:purge_dups
  biotoolsID: purge_dups
  collectionID:
  - ONTeater
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Dengfeng Guan
    note: null
    orcidid: https://orcid.org/0000-0002-6376-3940
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: https://www.chatlink.com.cn
  description: 'Identifying and removing haplotypic duplication in primary genome
    assemblies | haplotypic duplication identification tool | scripts/pd_config.py:
    script to generate a configuration file used by run_purge_dups.py | purge haplotigs
    and overlaps in an assembly based on read depth | Given a primary assembly pri_asm
    and an alternative assembly hap_asm (optional, if you have one), follow the steps
    shown below to build your own purge_dups pipeline, steps with same number can
    be run simultaneously. Among all the steps, although step 4 is optional, we highly
    recommend our users to do so, because assemblers may produce overrepresented seqeuences.
    In such a case, The final step 4 can be applied to remove those seqeuences'
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: null
    operation:
    - term: Genome assembly
      uri: http://edamontology.org/operation_0525
    - term: Read binning
      uri: http://edamontology.org/operation_3798
    - term: Scaffolding
      uri: http://edamontology.org/operation_3216
    output:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
  homepage: https://github.com/dfguan/purge_dups
  homepage_status: 0
  language:
  - Python
  - C
  lastUpdate: '2025-06-30T15:34:51.626796Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/dfguan/purge_dups
  - note: null
    type:
    - Issue tracker
    url: https://github.com/dfguan/purge_dups/issues
  maturity: null
  name: purge_dups
  operatingSystem:
  - Mac
  - Linux
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1101/729962
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType: []
  topic:
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  validated: 1
  version:
  - v.1.2.6
- accessibility: Open access
  additionDate: '2024-03-18T14:51:49.667412Z'
  biotoolsCURIE: biotools:compleasm
  biotoolsID: compleasm
  collectionID:
  - ONTeater
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: neng@ds.dfci.harvard.edu
    fundrefid: null
    gridid: null
    name: Neng Huang
    note: null
    orcidid: https://orcid.org/0000-0001-7187-0749
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  description: 'Compleasm: a faster and more accurate reimplementation of BUSCO.

    It provides measures for quantitative assessment of genome assembly, gene set,
    and transcriptome completeness based on evolutionarily informed expectations of
    gene content from near-universal single-copy orthologs.'
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/huangnengCSU/compleasm/blob/0.2.6/README.md
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: compleasm run -l "$lineage" -a assembly.fa -o output_prefix
    input:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTA-like
        uri: http://edamontology.org/format_2546
    note: Runs compleasm using the BUSCO set corresponding to the lineage given.
    operation:
    - term: Sequence assembly validation
      uri: http://edamontology.org/operation_3180
    output:
    - data:
        term: Sequence report
        uri: http://edamontology.org/data_2955
      format: []
  homepage: https://github.com/huangnengCSU/compleasm
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-06-30T15:30:41.266812Z'
  license: Apache-2.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/huangnengCSU/compleasm
  - note: null
    type:
    - Issue tracker
    url: https://github.com/huangnengCSU/compleasm/issues
  - note: List of accepted lineages (taxonomic groups with curated BUSCO sets)
    type:
    - Other
    url: https://busco.ezlab.org/list_of_lineages.html
  maturity: Mature
  name: Compleasm
  operatingSystem: []
  otherID: []
  owner: rlibouban
  publication:
  - doi: 10.1093/bioinformatics/btad595
    metadata:
      abstract: 'Motivation: Evaluating the gene completeness is critical to measuring
        the quality of a genome assembly. An incomplete assembly can lead to errors
        in gene predictions, annotation, and other downstream analyses. Benchmarking
        Universal Single-Copy Orthologs (BUSCO) is a widely used tool for assessing
        the completeness of genome assembly by testing the presence of a set of single-copy
        orthologs conserved across a wide range of taxa. However, BUSCO is slow particularly
        for large genome assemblies. It is cumbersome to apply BUSCO to a large number
        of assemblies. Results: Here, we present compleasm, an efficient tool for
        assessing the completeness of genome assemblies. Compleasm utilizes the miniprot
        protein-to-genome aligner and the conserved orthologous genes from BUSCO.
        It is 14 times faster than BUSCO for human assemblies and reports a more accurate
        completeness of 99.6% than BUSCO''s 95.7%, which is in close agreement with
        the annotation completeness of 99.5% for T2T-CHM13.'
      authors:
      - name: Huang N.
      - name: Li H.
      citationCount: 95
      date: '2023-10-01T00:00:00Z'
      journal: Bioinformatics
      title: 'compleasm: a faster and more accurate reimplementation of BUSCO'
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation:
  - biotoolsID: busco
    type: isNewVersionOf
  toolType:
  - Command-line tool
  topic:
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  - term: Transcriptomics
    uri: http://edamontology.org/topic_3308
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  validated: 0
  version:
  - v.0.2.5
- accessibility: Open access
  additionDate: '2016-09-30T15:59:05Z'
  biotoolsCURIE: biotools:silva
  biotoolsID: silva
  collectionID:
  - de.NBI
  - de.NBI-biodata
  - DSMZ Digital Diversity
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: hub@dsmz.de
    fundrefid: null
    gridid: grid.420081.f
    name: Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures
    note: null
    orcidid: null
    rorid: 02tyer376
    typeEntity: Institute
    typeRole:
    - Provider
    url: https://www.dsmz.de
  - email: contact@arb-silva.de
    fundrefid: null
    gridid: grid.507782.f
    name: SILVA Team
    note: null
    orcidid: null
    rorid: 027z9pz32
    typeEntity: Division
    typeRole:
    - Primary contact
    url: https://www.arb-silva.de/contact/team/
  description: SILVA provides comprehensive, quality checked and regularly updated
    datasets of aligned small (16S/18S, SSU) and large subunit (23S/28S, LSU) ribosomal
    RNA (rRNA) sequences for all three domains of life (Bacteria, Archaea and Eukaryota).
  documentation:
  - note: null
    type:
    - Terms of use
    url: https://www.arb-silva.de/silva-license-information/
  - note: null
    type:
    - Citation instructions
    url: https://www.arb-silva.de/contact/
  - note: null
    type:
    - General
    url: https://www.arb-silva.de/documentation/
  - note: null
    type:
    - FAQ
    url: https://www.arb-silva.de/documentation/faqs/
  download:
  - note: SILVA dataset archive
    type: Downloads page
    url: https://www.arb-silva.de/download/archive/
    version: null
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode:
  - Germany
  elixirPlatform:
  - Data
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Sequence accession (nucleic acid)
        uri: http://edamontology.org/data_1097
      format:
      - term: plain text format (unformatted)
        uri: http://edamontology.org/format_1964
    - data:
        term: Taxon
        uri: http://edamontology.org/data_1868
      format:
      - term: plain text format (unformatted)
        uri: http://edamontology.org/format_1964
    - data:
        term: Strain name
        uri: http://edamontology.org/data_1046
      format:
      - term: plain text format (unformatted)
        uri: http://edamontology.org/format_1964
    - data:
        term: Article ID
        uri: http://edamontology.org/data_1088
      format:
      - term: plain text format (unformatted)
        uri: http://edamontology.org/format_1964
    - data:
        term: Organism name
        uri: http://edamontology.org/data_2909
      format:
      - term: plain text format (unformatted)
        uri: http://edamontology.org/format_1964
    note: The search and retrieval functions of the SILVA website can be used to build
      custom subsets of sequences. In addition to simple searches e.g. for accession
      numbers, organism names, taxonomic entities, or publication DOI/PubMed IDs,
      complex queries over several database fields using constraints such as sequence
      length or quality values are possible. The results can be sorted according to
      accession numbers, organism names, sequence length, sequence and alignment quality
      and Pintail values. The search results show accession number, organism name,
      sequence length, sequence quality values, taxonomic classifications, and links
      to view the full sequence record on SILVA and on ENA. Sequences found via search
      and added to download cart can be downloaded as FASTA and ARB files.
    operation:
    - term: Query and retrieval
      uri: http://edamontology.org/operation_0224
    output:
    - data:
        term: Sequence report
        uri: http://edamontology.org/data_2955
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
    - data:
        term: Sequence alignment (nucleic acid)
        uri: http://edamontology.org/data_1383
      format:
      - term: ARB
        uri: http://edamontology.org/format_3830
      - term: FASTA-aln
        uri: http://edamontology.org/format_1984
    - data:
        term: Nucleic acid sequence
        uri: http://edamontology.org/data_2977
      format:
      - term: ARB
        uri: http://edamontology.org/format_3830
      - term: FASTA-aln
        uri: http://edamontology.org/format_1984
  - cmd: null
    input:
    - data:
        term: Nucleic acid sequence
        uri: http://edamontology.org/data_2977
      format:
      - term: nucleotide
        uri: http://edamontology.org/format_1207
    - data:
        term: PCR primers
        uri: http://edamontology.org/data_1240
      format:
      - term: nucleotide
        uri: http://edamontology.org/format_1207
    note: "The SILVA Probe Match and Evaluation Tool detects and displays all occurrences\
      \ of a given probe or primer sequence in the SILVA datasets. \n\nTestPrime allows\
      \ you to evaluate the performance of primer pairs by running an in silico PCR\
      \ on the SILVA databases. From the results of the PCR, TestPrime computes coverages\
      \ for each taxonomic group in all of the taxonomies offered by SILVA."
    operation:
    - term: Primer and probe design
      uri: http://edamontology.org/operation_2419
    output:
    - data:
        term: Report
        uri: http://edamontology.org/data_2048
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
      - term: HTML
        uri: http://edamontology.org/format_2331
    - data:
        term: Sequence set
        uri: http://edamontology.org/data_0850
      format:
      - term: Binary format
        uri: http://edamontology.org/format_2333
    - data:
        term: Nucleic acid sequence alignment
        uri: http://edamontology.org/data_1383
      format:
      - term: ARB
        uri: http://edamontology.org/format_3830
      - term: FASTA-aln
        uri: http://edamontology.org/format_1984
    - data:
        term: Nucleic acid sequence
        uri: http://edamontology.org/data_2977
      format:
      - term: ARB
        uri: http://edamontology.org/format_3830
      - term: FASTA-aln
        uri: http://edamontology.org/format_1984
  - cmd: null
    input:
    - data:
        term: Nucleic acid sequence
        uri: http://edamontology.org/data_2977
      format:
      - term: FASTA-aln
        uri: http://edamontology.org/format_1984
    note: The Alignment, Classification and Tree Service (ACT) of SILVA allows to
      align and optionally classify sequences using the SILVA Incremental Aligner
      (SINA). From aligned sequences, (optionally) phylogenetic trees can be inferred
      using FastTree or RAxML.
    operation:
    - term: Multiple sequence alignment
      uri: http://edamontology.org/operation_0492
    - term: Global alignment
      uri: http://edamontology.org/operation_0496
    - term: Taxonomic classification
      uri: http://edamontology.org/operation_3460
    - term: Phylogenetic inference (maximum likelihood and Bayesian methods)
      uri: http://edamontology.org/operation_0547
    output:
    - data:
        term: Nucleic acid sequence alignment
        uri: http://edamontology.org/data_1383
      format:
      - term: ARB
        uri: http://edamontology.org/format_3830
      - term: FASTA-aln
        uri: http://edamontology.org/format_1984
    - data:
        term: Sequence alignment report
        uri: http://edamontology.org/data_0867
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
      - term: Textual format
        uri: http://edamontology.org/format_2330
    - data:
        term: Phylogenetic tree
        uri: http://edamontology.org/data_0872
      format:
      - term: newick
        uri: http://edamontology.org/format_1910
    - data:
        term: Taxonomic classification
        uri: http://edamontology.org/data_1872
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
  homepage: https://www.arb-silva.de
  homepage_status: 0
  language: []
  lastUpdate: '2025-06-30T13:26:42.882897Z'
  license: CC-BY-4.0
  link:
  - note: SILVA Taxonomy Browser
    type:
    - Service
    url: https://www.arb-silva.de/browser/
  - note: SILVA metadata search
    type:
    - Service
    url: https://www.arb-silva.de/search/
  - note: 'ACT: Alignment, Classification and Tree Service'
    type:
    - Service
    url: https://www.arb-silva.de/aligner/
  - note: SILVA Probe Match and Evaluation Tool
    type:
    - Service
    url: https://www.arb-silva.de/search/testprobe/
  - note: SILVA Primer Evaluation Tool
    type:
    - Service
    url: https://www.arb-silva.de/search/testprime/
  - note: Web-based viewer for the SILVA guide trees
    type:
    - Service
    url: https://treeviewer.arb-silva.de/
  maturity: Mature
  name: SILVA rRNA database
  operatingSystem: []
  otherID:
  - type: rrid
    value: RRID:SCR_006423
    version: null
  owner: silva
  publication:
  - doi: 10.1093/nar/gks1219
    metadata:
      abstract: SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive
        web resource for up to date, quality-controlled databases of aligned ribosomal
        RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains
        and supplementary online services. The referred database release 111 (July
        2012) contains 3194 778 small subunit and 288717 large subunit rRNA gene sequences.
        Since the initial description of the project, substantial new features have
        been introduced, including advanced quality control procedures, an improved
        rRNA gene aligner, online tools for probe and primer evaluation and optimized
        browsing, searching and downloading on the website. Furthermore, the extensively
        curated SILVA taxonomy and the new non-redundant SILVA datasets provide an
        ideal reference for high-throughput classification of data from next-generation
        sequencing approaches. © The Author(s) 2012.
      authors:
      - name: Quast C.
      - name: Pruesse E.
      - name: Yilmaz P.
      - name: Gerken J.
      - name: Schweer T.
      - name: Yarza P.
      - name: Peplies J.
      - name: Glockner F.O.
      citationCount: 22633
      date: '2013-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'The SILVA ribosomal RNA gene database project: Improved data processing
        and web-based tools'
    note: null
    pmcid: PMC3531112
    pmid: '23193283'
    type:
    - Primary
    version: null
  - doi: 10.1093/nar/gkt1209
    metadata:
      abstract: SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive
        resource for up-to-date quality-controlled databases of aligned ribosomal
        RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains
        and supplementary online services. SILVA provides a manually curated taxonomy
        for all three domains of life, based on representative phylogenetic trees
        for the small- and large-subunit rRNA genes. This article describes the improvements
        the SILVA taxonomy has undergone in the last 3 years. Specifically we are
        focusing on the curation process, the various resources used for curation
        and the comparison of the SILVA taxonomy with Greengenes and RDP-II taxonomies.
        Our comparisons not only revealed a reasonable overlap between the taxa names,
        but also points to significant differences in both names and numbers of taxa
        between the three resources. © 2013 The Author(s). Published by Oxford University
        Press.
      authors:
      - name: Yilmaz P.
      - name: Parfrey L.W.
      - name: Yarza P.
      - name: Gerken J.
      - name: Pruesse E.
      - name: Quast C.
      - name: Schweer T.
      - name: Peplies J.
      - name: Ludwig W.
      - name: Glockner F.O.
      citationCount: 2590
      date: '2014-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: The SILVA and "all-species Living Tree Project (LTP)" taxonomic frameworks
    note: null
    pmcid: PMC3965112
    pmid: '24293649'
    type:
    - Other
    version: null
  - doi: 10.1093/nar/gkm864
    metadata:
      abstract: 'Sequencing ribosomal RNA (rRNA) genes is currently the method of
        choice for phylogenetic reconstruction, nucleic acid based detection and quantification
        of microbial diversity. The ARB software suite with its corresponding rRNA
        datasets has been accepted by researchers worldwide as a standard tool for
        large scale rRNA analysis. However, the rapid increase of publicly available
        rRNA sequence data has recently hampered the maintenance of comprehensive
        and curated rRNA knowledge databases. A new system, SILVA (from Latin silva,
        forest), was implemented to provide a central comprehensive web resource for
        up to date, quality controlled databases of aligned rRNA sequences from the
        Bacteria, Archaea and Eukarya domains. All sequences are checked for anomalies,
        carry a rich set of sequence associated contextual information, have multiple
        taxonomic classifications, and the latest validly described nomenclature.
        Furthermore, two precompiled sequence datasets compatible with ARB are offered
        for download on the SILVA website: (i) the reference (Ref) datasets, comprising
        only high quality, nearly full length sequences suitable for in-depth phylogenetic
        analysis and probe design and (ii) the comprehensive Parc datasets with all
        publicly available rRNA sequences longer than 300 nucleotides suitable for
        biodiversity analyses. The latest publicly available database release 91 (August
        2007) hosts 547 521 sequences split into 461 823 small subunit and 85 689
        large subunit rRNAs. © 2007 The Author(s).'
      authors:
      - name: Pruesse E.
      - name: Quast C.
      - name: Knittel K.
      - name: Fuchs B.M.
      - name: Ludwig W.
      - name: Peplies J.
      - name: Glockner F.O.
      citationCount: 5291
      date: '2007-12-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'SILVA: A comprehensive online resource for quality checked and aligned
        ribosomal RNA sequence data compatible with ARB'
    note: null
    pmcid: PMC2175337
    pmid: '17947321'
    type:
    - Other
    version: null
  - doi: 10.1093/bioinformatics/bts252
    metadata:
      abstract: 'Motivation: In the analysis of homologous sequences, computation
        of multiple sequence alignments (MSAs) has become a bottleneck. This is especially
        troublesome for marker genes like the ribosomal RNA (rRNA) where already millions
        of sequences are publicly available and individual studies can easily produce
        hundreds of thousands of new sequences. Methods have been developed to cope
        with such numbers, but further improvements are needed to meet accuracy requirements.Results:
        In this study, we present the SILVA Incremental Aligner (SINA) used to align
        the rRNA gene databases provided by the SILVA ribosomal RNA project. SINA
        uses a combination of k-mer searching and partial order alignment (POA) to
        maintain very high alignment accuracy while satisfying high throughput performance
        demands. SINA was evaluated in comparison with the commonly used high throughput
        MSA programs PyNAST and mothur. The three BRAliBase III benchmark MSAs could
        be reproduced with 99.3, 97.6 and 96.1 accuracy. A larger benchmark MSA comprising
        38 772 sequences could be reproduced with 98.9 and 99.3% accuracy using reference
        MSAs comprising 1000 and 5000 sequences. SINA was able to achieve higher accuracy
        than PyNAST and mothur in all performed benchmarks. © The Author(s) 2012.
        Published by Oxford University Press.'
      authors:
      - name: Pruesse E.
      - name: Peplies J.
      - name: Glockner F.O.
      citationCount: 2408
      date: '2012-07-01T00:00:00Z'
      journal: Bioinformatics
      title: 'SINA: Accurate high-throughput multiple sequence alignment of ribosomal
        RNA genes'
    note: null
    pmcid: PMC3389763
    pmid: '22556368'
    type:
    - Other
    version: null
  - doi: 10.1016/j.jbiotec.2017.06.1198
    metadata:
      abstract: SILVA (lat. forest) is a comprehensive web resource, providing services
        around up to date, high-quality datasets of aligned ribosomal RNA gene (rDNA)
        sequences from the Bacteria, Archaea, and Eukaryota domains. SILVA dates back
        to the year 1991 when Dr. Wolfgang Ludwig from the Technical University Munich
        started the integrated software workbench ARB (lat. tree) to support high-quality
        phylogenetic inference and taxonomy based on the SSU and LSU rDNA marker genes.
        At that time, the ARB project maintained both, the sequence reference datasets
        and the software package for data analysis. In 2005, with the massive increase
        of DNA sequence data, the maintenance of the software system ARB and the corresponding
        rRNA databases SILVA was split between Munich and the Microbial Genomics and
        Bioinformatics Research Group in Bremen. ARB has been continuously developed
        to include new features and improve the usability of the workbench. Thousands
        of users worldwide appreciate the seamless integration of common analysis
        tools under a central graphical user interface, in combination with its versatility.
        The first SILVA release was deployed in February 2007 based on the EMBL-EBI/ENA
        release 89. Since then, full SILVA releases offering the database content
        in various flavours are published at least annually, complemented by intermediate
        web-releases where only the SILVA web dataset is updated. SILVA is the only
        rDNA database project worldwide where special emphasis is given to the consistent
        naming of clades of uncultivated (environmental) sequences, where no validly
        described cultivated representatives are available. Also exclusive for SILVA
        is the maintenance of both comprehensive aligned 16S/18S rDNA and 23S/28S
        rDNA sequence datasets. Furthermore, the SILVA alignments and trees were designed
        to include Eukaryota, another unique feature among rDNA databases. With the
        termination of the European Ribosomal RNA Database Project in 2007, the SILVA
        database has become the authoritative rDNA database project for Europe. The
        application spectrum of ARB and SILVA ranges from biodiversity analysis, medical
        diagnostics, to biotechnology and quality control for academia and industry.
      authors:
      - name: Glockner F.O.
      - name: Yilmaz P.
      - name: Quast C.
      - name: Gerken J.
      - name: Beccati A.
      - name: Ciuprina A.
      - name: Bruns G.
      - name: Yarza P.
      - name: Peplies J.
      - name: Westram R.
      - name: Ludwig W.
      citationCount: 635
      date: '2017-11-10T00:00:00Z'
      journal: Journal of Biotechnology
      title: 25 years of serving the community with ribosomal RNA gene reference databases
        and tools
    note: null
    pmcid: null
    pmid: '28648396'
    type:
    - Review
    version: null
  - doi: 10.1186/s12859-017-1841-3
    metadata:
      abstract: 'Background: Phylogenetic trees are an important tool to study the
        evolutionary relationships among organisms. The huge amount of available taxa
        poses difficulties in their interactive visualization. This hampers the interaction
        with the users to provide feedback for the further improvement of the taxonomic
        framework. Results: The SILVA Tree Viewer is a web application designed for
        visualizing large phylogenetic trees without requiring the download of any
        software tool or data files. The SILVA Tree Viewer is based on Web Geographic
        Information Systems (Web-GIS) technology with a PostgreSQL backend. It enables
        zoom and pan functionalities similar to Google Maps. The SILVA Tree Viewer
        enables access to two phylogenetic (guide) trees provided by the SILVA database:
        the SSU Ref NR99 inferred from high-quality, full-length small subunit sequences,
        clustered at 99% sequence identity and the LSU Ref inferred from high-quality,
        full-length large subunit sequences. Conclusions: The Tree Viewer provides
        tree navigation, search and browse tools as well as an interactive feedback
        system to collect any kinds of requests ranging from taxonomy to data curation
        and improving the tool itself.'
      authors:
      - name: Beccati A.
      - name: Gerken J.
      - name: Quast C.
      - name: Yilmaz P.
      - name: Glockner F.O.
      citationCount: 29
      date: '2017-09-30T00:00:00Z'
      journal: BMC Bioinformatics
      title: 'SILVA tree viewer: Interactive web browsing of the SILVA phylogenetic
        guide trees'
    note: null
    pmcid: null
    pmid: null
    type:
    - Other
    version: null
  relation:
  - biotoolsID: silvangs
    type: usedBy
  - biotoolsID: d3hub
    type: includedIn
  toolType:
  - Web application
  - Database portal
  topic:
  - term: Functional, regulatory and non-coding RNA
    uri: http://edamontology.org/topic_0659
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  - term: Phylogenetics
    uri: http://edamontology.org/topic_3293
  - term: Taxonomy
    uri: http://edamontology.org/topic_0637
  - term: Biodiversity
    uri: http://edamontology.org/topic_3050
  - term: Microbiology
    uri: http://edamontology.org/topic_3301
  - term: Probes and primers
    uri: http://edamontology.org/topic_0632
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2025-06-30T08:52:48.500476Z'
  biotoolsCURIE: biotools:fair_eva_4_eucaim
  biotoolsID: fair_eva_4_eucaim
  collectionID:
  - EUCAIM
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: European Union’s Horizon 2020 research and innovation programme
    note: This software started to be developed within IFCA-Advanced-Computing receives
      funding from the European Union’s Horizon 2020 research and innovation programme
      under grant agreement No 857647.
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  description: 'FAIR EVA: Evaluator, Validator & Advisor has been developed to check
    the FAIRness level of digital objects from different repositories or data portals.
    It requires the object identifier (preferably persistent and unique identifier)
    and the repository to check. It also provides a generic and agnostic way to check
    digital objects.'
  documentation:
  - note: Documentation for the main package, EUCAIM plugin specific documentation
      not included.
    type:
    - Quick start guide
    url: https://github.com/IFCA-Advanced-Computing/FAIR_eva/blob/main/docs/index.md
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function: []
  homepage: https://github.com/IFCA-Advanced-Computing/FAIR_eva
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-06-30T09:00:26.819772Z'
  license: Apache-2.0
  link: []
  maturity: Mature
  name: FAIR_EVA
  operatingSystem:
  - Linux
  otherID: []
  owner: davrodgon
  publication:
  - doi: 10.1038/s41597-023-02652-8
    metadata:
      abstract: The FAIR Principles are a set of good practices to improve the reproducibility
        and quality of data in an Open Science context. Different sets of indicators
        have been proposed to evaluate the FAIRness of digital objects, including
        datasets that are usually stored in repositories or data portals. However,
        indicators like those proposed by the Research Data Alliance are provided
        from a high-level perspective that can be interpreted and they are not always
        realistic to particular environments like multidisciplinary repositories.
        This paper describes FAIR EVA, a new tool developed within the European Open
        Science Cloud context that is oriented to particular data management systems
        like open repositories, which can be customized to a specific case in a scalable
        and automatic environment. It aims to be adaptive enough to work for different
        environments, repository software and disciplines, taking into account the
        flexibility of the FAIR Principles. As an example, we present DIGITAL.CSIC
        repository as the first target of the tool, gathering the particular needs
        of a multidisciplinary institution as well as its institutional repository.
      authors:
      - name: Aguilar Gomez F.
      - name: Bernal I.
      citationCount: 6
      date: '2023-12-01T00:00:00Z'
      journal: Scientific Data
      title: 'FAIR EVA: Bringing institutional multidisciplinary repositories into
        the FAIR picture'
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType:
  - Web service
  - Script
  topic:
  - term: FAIR data
    uri: http://edamontology.org/topic_4012
  validated: 0
  version:
  - EUCAIM_plugin_1
- accessibility: Open access
  additionDate: '2024-07-12T13:51:31.192159Z'
  biotoolsCURIE: biotools:fantasia
  biotoolsID: fantasia
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: FANTASIA (Functional ANnoTAtion based on embedding space SImilArity)
    is a pipeline for annotating GO terms in protein sequence files using GOPredSim
    with the protein language model ProtT5
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein structure alignment
        uri: http://edamontology.org/data_1481
      format: []
    note: null
    operation:
    - term: Phylogenetic analysis
      uri: http://edamontology.org/operation_0324
    - term: Gene functional annotation
      uri: http://edamontology.org/operation_3672
    output: []
  homepage: https://github.com/MetazoaPhylogenomicsLab/FANTASIA
  homepage_status: 0
  language: []
  lastUpdate: '2025-06-28T15:45:24.390300Z'
  license: null
  link: []
  maturity: null
  name: FANTASIA
  operatingSystem: []
  otherID: []
  owner: arojas
  publication:
  - doi: 10.1101/2024.02.28.582465
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  - doi: 10.1101/2024.02.14.580341
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Proteins
    uri: http://edamontology.org/topic_0078
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  validated: 0
  version:
  - 2.1.0
- accessibility: Open access
  additionDate: '2019-08-26T14:34:55Z'
  biotoolsCURIE: biotools:MINERVA_Platform
  biotoolsID: MINERVA_Platform
  collectionID:
  - ELIXIR-LU
  - LCSB
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: 'The MINERVA (Molecular Interaction NEtwoRk VisuAlization) platform
    is a standalone webserver for visualization, exploration and management of molecular
    networks encoded in SBGN-compliant format, including files produced using CellDesigner
    or SBGN editors. Visualization of uploaded networks generated by the platform
    is accessible via a web browser to all viewers with the weblink to the resource.


    The MINERVA Platform is a webservice using the Java Server Faces 2 technology.
    The server side, including data parsing, integration, annotation and verification,
    is implemented in Java. The platform uses the Postgres SQL database for data storage
    and the Hibernate framework as a middle layer between web server and database.
    The user web-interface is generated using React.js. The displayed content is visualized
    by OpenLayers API, dedicated JavaScript and CSS.'
  documentation:
  - note: null
    type:
    - Quick start guide
    - Release notes
    - User manual
    - API documentation
    - Citation instructions
    - Terms of use
    url: https://minerva.uni.lu
  download:
  - note: Installation instructions, including debian package, virtual machine images
      and docker containers.
    type: Other
    url: https://minerva.pages.uni.lu/doc/install/
    version: 13.1.3 - 18.1.1
  editPermission:
    authors:
    - sascha.herzinger
    type: group
  elixirCommunity: []
  elixirNode:
  - Luxembourg
  elixirPlatform:
  - Tools
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: Visualise systems biology diagrams online, on a standalone web server
    operation:
    - term: Pathway visualisation
      uri: http://edamontology.org/operation_3926
    output: []
  - cmd: null
    input: []
    note: Visualise omics data from multiple datasets on top of the diagrams
    operation:
    - term: Expression data visualisation
      uri: http://edamontology.org/operation_0571
    output: []
  - cmd: null
    input: []
    note: 'Convert between main systems biology layout formats: CellDeslgners SBML,
      SBML layout+render, SBGN-ML, GPML'
    operation:
    - term: Conversion
      uri: http://edamontology.org/operation_3434
    output: []
  - cmd: null
    input: []
    note: Use MINERVA API to access systems biology formats for modelling
    operation:
    - term: Modelling and simulation
      uri: http://edamontology.org/operation_2426
    output: []
  homepage: https://minerva.uni.lu
  homepage_status: 0
  language: []
  lastUpdate: '2025-06-26T13:15:59.673112Z'
  license: AGPL-3.0
  link:
  - note: GiLab repository for core functionalities (data and format handling, service
      stability, API access)
    type:
    - Repository
    url: https://gitlab.lcsb.uni.lu/minerva/core/
  - note: Issue tracker for core functionalities (data and format handling, service
      stability, API access)
    type:
    - Issue tracker
    url: https://gitlab.lcsb.uni.lu/minerva/core/-/issues
  - note: GiLab repository for frontend functionalities
    type:
    - Repository
    url: https://gitlab.lcsb.uni.lu/minerva/frontend
  - note: Issue tracker for frontend functionalities
    type:
    - Issue tracker
    url: https://gitlab.lcsb.uni.lu/minerva/frontend/-/issues
  maturity: Mature
  name: The MINERVA Platform
  operatingSystem: []
  otherID: []
  owner: mjostaszewski
  publication:
  - doi: 10.1038/npjsba.2016.20
    metadata:
      abstract: Our growing knowledge about various molecular mechanisms is becoming
        increasingly more structured and accessible. Different repositories of molecular
        interactions and available literature enable construction of focused and high-quality
        molecular interaction networks. Novel tools for curation and exploration of
        such networks are needed, in order to foster the development of a systems
        biology environment. In particular, solutions for visualization, annotation
        and data cross-linking will facilitate usage of network-encoded knowledge
        in biomedical research. To this end we developed the MINERVA (Molecular Interaction
        NEtwoRks VisuAlization) platform, a standalone webservice supporting curation,
        annotation and visualization of molecular interaction networks in Systems
        Biology Graphical Notation (SBGN)-compliant format. MINERVA provides automated
        content annotation and verification for improved quality control. The end
        users can explore and interact with hosted networks, and provide direct feedback
        to content curators. MINERVA enables mapping drug targets or overlaying experimental
        data on the visualized networks. Extensive export functions enable downloading
        areas of the visualized networks as SBGN-compliant models for efficient reuse
        of hosted networks. The software is available under Affero GPL 3.0 as a Virtual
        Machine snapshot, Debian package and Docker instance at http://r3lab.uni.lu/web/minerva-website/.
        We believe that MINERVA is an important contribution to systems biology community,
        as its architecture enables set-up of locally or globally accessible SBGN-oriented
        repositories of molecular interaction networks. Its functionalities allow
        overlay of multiple information layers, facilitating exploration of content
        and interpretation of data. Moreover, annotation and verification workflows
        of MINERVA improve the efficiency of curation of networks, allowing life-science
        researchers to better engage in development and use of biomedical knowledge
        repositories.
      authors:
      - name: Gawron P.
      - name: Ostaszewski M.
      - name: Satagopam V.
      - name: Gebel S.
      - name: Mazein A.
      - name: Kuzma M.
      - name: Zorzan S.
      - name: McGee F.
      - name: Otjacques B.
      - name: Balling R.
      - name: Schneider R.
      citationCount: 65
      date: '2016-01-01T00:00:00Z'
      journal: npj Systems Biology and Applications
      title: MINERVA—A platform for visualization and curation of molecular interaction
        networks
    note: null
    pmcid: PMC5516855
    pmid: '28725475'
    type:
    - Primary
    version: '10.0'
  - doi: 10.1093/bioinformatics/btz286
    metadata:
      abstract: 'Summary: The complexity of molecular networks makes them difficult
        to navigate and interpret, creating a need for specialized software. MINERVA
        is a web platform for visualization, exploration and management of molecular
        networks. Here, we introduce an extension to MINERVA architecture that greatly
        facilitates the access and use of the stored molecular network data. It allows
        to incorporate such data in analytical pipelines via a programmatic access
        interface, and to extend the platform''s visual exploration and analytics
        functionality via plugin architecture. This is possible for any molecular
        network hosted by the MINERVA platform encoded in well-recognized systems
        biology formats. To showcase the possibilities of the plugin architecture,
        we have developed several plugins extending the MINERVA core functionalities.
        In the article, we demonstrate the plugins for interactive tree traversal
        of molecular networks, for enrichment analysis and for mapping and visualization
        of known disease variants or known adverse drug reactions to molecules in
        the network. Availability and implementation: Plugins developed and maintained
        by the MINERVA team are available under the AGPL v3 license at https://git-r3lab.uni.lu/minerva/plugins/.
        The MINERVA API and plugin documentation is available at https://minerva-web.lcsb.uni.lu.'
      authors:
      - name: Hoksza D.
      - name: Gawron P.
      - name: Ostaszewski M.
      - name: Smula E.
      - name: Schneider R.
      citationCount: 25
      date: '2019-11-01T00:00:00Z'
      journal: Bioinformatics
      title: 'MINERVA API and plugins: Opening molecular network analysis and visualization
        to the community'
    note: null
    pmcid: PMC6821317
    pmid: '31074494'
    type:
    - Primary
    version: 12.2.3
  - doi: 10.1093/bib/bbz067
    metadata:
      abstract: The understanding of complex biological networks often relies on both
        a dedicated layout and a topology. Currently, there are three major competing
        layout-aware systems biology formats, but there are no software tools or software
        libraries supporting all of them. This complicates the management of molecular
        network layouts and hinders their reuse and extension. In this paper, we present
        a high-level overview of the layout formats in systems biology, focusing on
        their commonalities and differences, review their support in existing software
        tools, libraries and repositories and finally introduce a new conversion module
        within the MINERVA platform. The module is available via a REST API and offers,
        besides the ability to convert between layout-aware systems biology formats,
        the possibility to export layouts into several graphical formats. The module
        enables conversion of very large networks with thousands of elements, such
        as disease maps or metabolic reconstructions, rendering it widely applicable
        in systems biology.
      authors:
      - name: Hoksza D.
      - name: Gawron P.
      - name: Ostaszewski M.
      - name: Hasenauer J.
      - name: Schneider R.
      citationCount: 17
      date: '2019-07-10T00:00:00Z'
      journal: Briefings in Bioinformatics
      title: Closing the gap between formats for storing layout information in systems
        biology
    note: null
    pmcid: PMC7373180
    pmid: '31273380'
    type:
    - Primary
    version: 13.1.1
  - doi: 10.1089/big.2015.0057
    metadata:
      abstract: Translational medicine is a domain turning results of basic life science
        research into new tools and methods in a clinical environment, for example,
        as new diagnostics or therapies. Nowadays, the process of translation is supported
        by large amounts of heterogeneous data ranging from medical data to a whole
        range of -omics data. It is not only a great opportunity but also a great
        challenge, as translational medicine big data is difficult to integrate and
        analyze, and requires the involvement of biomedical experts for the data processing.
        We show here that visualization and interoperable workflows, combining multiple
        complex steps, can address at least parts of the challenge. In this article,
        we present an integrated workflow for exploring, analysis, and interpretation
        of translational medicine data in the context of human health. Three Web services
        - tranSMART, a Galaxy Server, and a MINERVA platform - are combined into one
        big data pipeline. Native visualization capabilities enable the biomedical
        experts to get a comprehensive overview and control over separate steps of
        the workflow. The capabilities of tranSMART enable a flexible filtering of
        multidimensional integrated data sets to create subsets suitable for downstream
        processing. A Galaxy Server offers visually aided construction of analytical
        pipelines, with the use of existing or custom components. A MINERVA platform
        supports the exploration of health and disease-related mechanisms in a contextualized
        analytical visualization system. We demonstrate the utility of our workflow
        by illustrating its subsequent steps using an existing data set, for which
        we propose a filtering scheme, an analytical pipeline, and a corresponding
        visualization of analytical results. The workflow is available as a sandbox
        environment, where readers can work with the described setup themselves. Overall,
        our work shows how visualization and interfacing of big data processing services
        facilitate exploration, analysis, and interpretation of translational medicine
        data.
      authors:
      - name: Satagopam V.
      - name: Gu W.
      - name: Eifes S.
      - name: Gawron P.
      - name: Ostaszewski M.
      - name: Gebel S.
      - name: Barbosa-Silva A.
      - name: Balling R.
      - name: Schneider R.
      citationCount: 39
      date: '2016-06-01T00:00:00Z'
      journal: Big Data
      title: Integration and Visualization of Translational Medicine Data for Better
        Understanding of Human Diseases
    note: null
    pmcid: PMC4932659
    pmid: '27441714'
    type:
    - Usage
    version: '10.0'
  - doi: 10.1016/j.envpol.2019.04.005
    metadata:
      abstract: 'Polychlorinated biphenyls (PCBs) are a class of widespread environmental
        pollutants, commonly found in human blood, that have been suggested to be
        linked to the occurrence of sporadic Parkinson''s disease (PD). It has been
        reported that some non-coplanar PCBs accumulate in the brains of female PD
        patients. To improve our understanding of the association between PCB exposure
        and PD risk we have applied whole transcriptome gene expression analysis in
        blood cells from 594 PCB-exposed subjects (369 female, 225 male). Interestingly,
        we observe that in females, blood levels of non-coplanar PCBs appear to be
        associated with expression levels of PD-specific genes. However, no such association
        was detected in males. Among the 131 PD-specific genes affected, 39 have been
        shown to display similar changes in expression levels in the substantia nigra
        of deceased PD patients. Especially among the down-regulated genes, transcripts
        of genes involved in neurotransmitter vesicle-related functions were predominant.
        Capsule: Plasma PCB levels are associated with gene expression changes in
        females only, resulting in brain-related genes changing in blood cells of
        healthy individuals exposed to PCBs.'
      authors:
      - name: Bohler S.
      - name: Krauskopf J.
      - name: Espin-Perez A.
      - name: Gebel S.
      - name: Palli D.
      - name: Rantakokko P.
      - name: Kiviranta H.
      - name: Kyrtopoulos S.A.
      - name: Balling R.
      - name: Kleinjans J.
      citationCount: 5
      date: '2019-07-01T00:00:00Z'
      journal: Environmental Pollution
      title: Genes associated with Parkinson's disease respond to increasing polychlorinated
        biphenyl levels in the blood of healthy females
    note: null
    pmcid: null
    pmid: '30991279'
    type: []
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  - term: Omics
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  - term: Translational medicine
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  - term: Systems biology
    uri: http://edamontology.org/topic_2259
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  - 13.2.0
  - 14.0.13
  - 15.0.3
  - 16.4.0
  - 17.1.3
  - 18.1.1
- accessibility: Open access
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  biotoolsCURIE: biotools:fantasiav2
  biotoolsID: fantasiav2
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    name: Ana M Rojas Mendoza
    note: Scientific concept and functionalities
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    url: https://www.metazomics.com/
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    rorid: null
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  - email: gemma.martinez@ibe.upf-csic.es
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    name: Gemma Martinez Redondo
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    orcidid: null
    rorid: null
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    url: https://www.metazomics.com/
  description: FANTASIA (Functional ANnoTAtion based on embedding space SImilArity)
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    and provide enhanced functionalities.
  documentation:
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    - General
    url: https://fantasia.readthedocs.io/en/latest/
  download: []
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  - Python
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  license: MIT
  link:
  - note: Main repository contains documentation  from latest version
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    - Repository
    url: https://github.com/CBBIO/FANTASIA
  - note: Main repository contains documentation  from linitial version based on Bioembeddings
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    url: https://github.com/MetazoaPhylogenomicsLab/FANTASIA
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    type:
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      abstract: Protein language models have been tested and proved to be reliable
        when used on curated datasets but have not yet been applied to full proteomes.
        Accordingly, we tested how two different machine learning-based methods performed
        when decoding functional information from the proteomes of selected model
        organisms. We found that protein language models are more precise and informative
        than deep learning methods for all the species tested and across the three
        gene ontologies studied, and that they better recover functional information
        from transcriptomic experiments. The results obtained indicate that these
        language models are likely to be suitable for large-scale annotation and downstream
        analyses, and we recommend a guide for their use.
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      - name: Barrios-Nunez I.
      - name: Martinez-Redondo G.I.
      - name: Medina-Burgos P.
      - name: Cases I.
      - name: Fernandez R.
      - name: Rojas A.M.
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      title: Decoding functional proteome information in model organisms using protein
        language models
    note: null
    pmcid: null
    pmid: null
    type:
    - Usage
    version: null
  - doi: 10.1101/2024.02.28.582465
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
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  - term: Molecular evolution
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  - term: Natural language processing
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  - term: Functional genomics
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  - term: Open science
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  - email: pierluigi.martelli@unibo.it
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  description: Prediction of secretory signal peptides in protein sequences
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    - data:
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      - term: Textual format
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    note: null
    operation:
    - term: Protein signal peptide detection
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    output:
    - data:
        term: Protein report
        uri: http://edamontology.org/data_0896
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
  homepage: https://busca.biocomp.unibo.it/deepsig/
  homepage_status: 0
  language:
  - Python
  - C++
  lastUpdate: '2025-06-19T11:55:09.017105Z'
  license: GPL-3.0
  link: []
  maturity: Mature
  name: DeepSig
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  - Windows
  - Mac
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  owner: ELIXIR-ITA-BOLOGNA
  publication:
  - doi: 10.1093/bioinformatics/btx818
    metadata:
      abstract: Motivation The identification of signal peptides in protein sequences
        is an important step toward protein localization and function characterization.
        Results Here, we present DeepSig, an improved approach for signal peptide
        detection and cleavage-site prediction based on deep learning methods. Comparative
        benchmarks performed on an updated independent dataset of proteins show that
        DeepSig is the current best performing method, scoring better than other available
        state-of-the-art approaches on both signal peptide detection and precise cleavage-site
        identification. Availability and implementation DeepSig is available as both
        standalone program and web server at https://deepsig.biocomp.unibo.it. All
        datasets used in this study can be obtained from the same website.
      authors:
      - name: Savojardo C.
      - name: Martelli P.L.
      - name: Fariselli P.
      - name: Casadio R.
      citationCount: 96
      date: '2018-05-15T00:00:00Z'
      journal: Bioinformatics
      title: 'DeepSig: Deep learning improves signal peptide detection in proteins'
    note: null
    pmcid: PMC5946842
    pmid: '29280997'
    type:
    - Primary
    version: '1.0'
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  toolType:
  - Web application
  - Command-line tool
  topic:
  - term: Computational biology
    uri: http://edamontology.org/topic_3307
  - term: Protein sites, features and motifs
    uri: http://edamontology.org/topic_3510
  - term: Protein properties
    uri: http://edamontology.org/topic_0123
  validated: 1
  version:
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- accessibility: Open access
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  biotoolsCURIE: biotools:qiime2
  biotoolsID: qiime2
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit:
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    fundrefid: null
    gridid: null
    name: Greg Caporaso
    note: null
    orcidid: https://orcid.org/0000-0002-8865-1670
    rorid: null
    typeEntity: null
    typeRole:
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    url: https://cap-lab.bio
  description: QIIME 2 is an AI-ready microbiome multi-omics data science platform
    that is trusted, free, open source, extensible, and community developed and supported
    bioinformatics.
  documentation:
  - note: User documentation for amplicon analysis, oriented to new users.
    type:
    - General
    url: https://amplicon-docs.qiime2.org
  - note: User documentation for metagenome analysis, oriented to new users.
    type:
    - Installation instructions
    url: https://moshpit.qiime2.org
  - note: User documentation, oriented toward power users.
    type:
    - User manual
    url: https://use.qiime2.org
  - note: Developer documentation, including a plugin development tutorial.
    type:
    - API documentation
    url: https://develop.qiime2.org
  - note: 'The QIIME 2 Library Stacks: a resource for discovering relevant documentation.'
    type:
    - Other
    url: https://library.qiime2.org/books
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  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Demultiplexing
      uri: http://edamontology.org/operation_3933
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    - term: Taxonomic classification
      uri: http://edamontology.org/operation_3460
    output: []
  homepage: https://qiime2.org
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-06-18T21:00:46.185472Z'
  license: BSD-3-Clause
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/qiime2
  - note: null
    type:
    - Software catalogue
    url: https://library.qiime2.org
  - note: null
    type:
    - Discussion forum
    url: https://forum.qiime2.org
  - note: Site for viewing and interacting with QIIME 2 results.
    type:
    - Other
    url: https://view.qiime2.org
  maturity: Mature
  name: QIIME 2
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: gregcaporaso
  publication:
  - doi: 10.1038/s41587-019-0209-9
    metadata:
      abstract: ''
      authors:
      - name: Bolyen E.
      - name: Rideout J.R.
      - name: Dillon M.R.
      - name: Bokulich N.A.
      - name: Abnet C.C.
      - name: Al-Ghalith G.A.
      - name: Alexander H.
      - name: Alm E.J.
      - name: Arumugam M.
      - name: Asnicar F.
      - name: Bai Y.
      - name: Bisanz J.E.
      - name: Bittinger K.
      - name: Brejnrod A.
      - name: Brislawn C.J.
      - name: Brown C.T.
      - name: Callahan B.J.
      - name: Caraballo-Rodriguez A.M.
      - name: Chase J.
      - name: Cope E.K.
      - name: Da Silva R.
      - name: Diener C.
      - name: Dorrestein P.C.
      - name: Douglas G.M.
      - name: Durall D.M.
      - name: Duvallet C.
      - name: Edwardson C.F.
      - name: Ernst M.
      - name: Estaki M.
      - name: Fouquier J.
      - name: Gauglitz J.M.
      - name: Gibbons S.M.
      - name: Gibson D.L.
      - name: Gonzalez A.
      - name: Gorlick K.
      - name: Guo J.
      - name: Hillmann B.
      - name: Holmes S.
      - name: Holste H.
      - name: Huttenhower C.
      - name: Huttley G.A.
      - name: Janssen S.
      - name: Jarmusch A.K.
      - name: Jiang L.
      - name: Kaehler B.D.
      - name: Kang K.B.
      - name: Keefe C.R.
      - name: Keim P.
      - name: Kelley S.T.
      - name: Knights D.
      - name: Koester I.
      - name: Kosciolek T.
      - name: Kreps J.
      - name: Langille M.G.I.
      - name: Lee J.
      - name: Ley R.
      - name: Liu Y.-X.
      - name: Loftfield E.
      - name: Lozupone C.
      - name: Maher M.
      - name: Marotz C.
      - name: Martin B.D.
      - name: McDonald D.
      - name: McIver L.J.
      - name: Melnik A.V.
      - name: Metcalf J.L.
      - name: Morgan S.C.
      - name: Morton J.T.
      - name: Naimey A.T.
      - name: Navas-Molina J.A.
      - name: Nothias L.F.
      - name: Orchanian S.B.
      - name: Pearson T.
      - name: Peoples S.L.
      - name: Petras D.
      - name: Preuss M.L.
      - name: Pruesse E.
      - name: Rasmussen L.B.
      - name: Rivers A.
      - name: Robeson M.S.
      - name: Rosenthal P.
      - name: Segata N.
      - name: Shaffer M.
      - name: Shiffer A.
      - name: Sinha R.
      - name: Song S.J.
      - name: Spear J.R.
      - name: Swafford A.D.
      - name: Thompson L.R.
      - name: Torres P.J.
      - name: Trinh P.
      - name: Tripathi A.
      - name: Turnbaugh P.J.
      - name: Ul-Hasan S.
      - name: van der Hooft J.J.J.
      - name: Vargas F.
      - name: Vazquez-Baeza Y.
      - name: Vogtmann E.
      - name: von Hippel M.
      - name: Walters W.
      - name: Wan Y.
      - name: Wang M.
      - name: Warren J.
      - name: Weber K.C.
      - name: Williamson C.H.D.
      - name: Willis A.D.
      - name: Xu Z.Z.
      - name: Zaneveld J.R.
      - name: Zhang Y.
      - name: Zhu Q.
      - name: Knight R.
      - name: Caporaso J.G.
      citationCount: 14289
      date: '2019-08-01T00:00:00Z'
      journal: Nature Biotechnology
      title: Reproducible, interactive, scalable and extensible microbiome data science
        using QIIME 2
    note: null
    pmcid: PMC7015180
    pmid: '31341288'
    type:
    - Primary
    version: '2.0'
  relation:
  - biotoolsID: qiime
    type: isNewVersionOf
  toolType:
  - Suite
  - Command-line tool
  - Library
  topic:
  - term: Microbial ecology
    uri: http://edamontology.org/topic_3697
  - term: Metatranscriptomics
    uri: http://edamontology.org/topic_3941
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  validated: 0
  version:
  - '2.0'
- accessibility: Open access
  additionDate: '2025-06-17T20:53:54.551980Z'
  biotoolsCURIE: biotools:metasbt
  biotoolsID: metasbt
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: fabio.cumbo@gmail.com
    fundrefid: null
    gridid: null
    name: Fabio Cumbo
    note: null
    orcidid: https://orcid.org/0000-0003-2920-5838
    rorid: null
    typeEntity: null
    typeRole:
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    - Developer
    - Maintainer
    - Support
    url: https://cumbof.github.io
  description: MetaSBT is a scalable framework designed to automatically index microbial
    genomes and accurately characterize metagenome-assembled genomes using Sequence
    Bloom Trees.
  documentation:
  - note: Official MetaSBT Wiki
    type:
    - General
    url: https://github.com/cumbof/MetaSBT/wiki
  download:
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    type: Software package
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  additionDate: '2021-07-06T20:27:27Z'
  biotoolsCURIE: biotools:nanoplot
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    fundrefid: null
    gridid: null
    name: Wouter De Coster
    note: null
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  description: NanoPlot is a tool with various visualizations of sequencing data in
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  - note: null
    type:
    - Command-line options
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  download:
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  - note: null
    type: Command-line specification
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  function:
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    input:
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      format:
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      - term: nucleotide
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    note: null
    operation:
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    - term: Box-Whisker plot plotting
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    output: []
  homepage: https://github.com/wdecoster/NanoPlot
  homepage_status: 0
  language:
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  lastUpdate: '2025-06-18T12:31:48.762608Z'
  license: GPL-3.0
  link:
  - note: Issue tracker and most up to date software version
    type:
    - Repository
    url: https://github.com/wdecoster/NanoPlot
  - note: Web service with more limited options compared to the command line tool
    type:
    - Service
    url: http://nanoplot.bioinf.be/
  maturity: Mature
  name: NanoPlot
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: wdecoster
  publication:
  - doi: 10.1093/bioinformatics/bty149
    metadata:
      abstract: 'Summary: Here we describe NanoPack, a set of tools developed for
        visualization and processing of long-read sequencing data from Oxford Nanopore
        Technologies and Pacific Biosciences. Availability and implementation: The
        NanoPack tools are written in Python3 and released under the GNU GPL3.0 License.
        The source code can be found at https://github.com/wdecoster/nanopack, together
        with links to separate scripts and their documentation. The scripts are compatible
        with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available
        as a graphical user interface, a web service at http://nanoplot.bioinf.be
        and command line tools.'
      authors:
      - name: De Coster W.
      - name: D'Hert S.
      - name: Schultz D.T.
      - name: Cruts M.
      - name: Van Broeckhoven C.
      citationCount: 1840
      date: '2018-08-01T00:00:00Z'
      journal: Bioinformatics
      title: 'NanoPack: Visualizing and processing long-read sequencing data'
    note: null
    pmcid: PMC6061794
    pmid: '29547981'
    type:
    - Method
    version: null
  relation:
  - biotoolsID: nanopack
    type: includedIn
  toolType:
  - Command-line tool
  - Web application
  topic:
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  validated: 0
  version:
  - v.1.42.0
- accessibility: Open access
  additionDate: '2019-09-13T12:51:16Z'
  biotoolsCURIE: biotools:kraken2
  biotoolsID: kraken2
  collectionID:
  - ONTeater
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Derrick E. Wood
    note: null
    orcidid: http://orcid.org/0000-0002-7429-1854
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Jennifer Lu
    note: null
    orcidid: http://orcid.org/0000-0001-9167-2002
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: langmea@cs.jhu.edu
    fundrefid: null
    gridid: null
    name: Ben Langmead
    note: null
    orcidid: http://orcid.org/0000-0003-2437-1976
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: 'Kraken 2 is the newest version of Kraken, a taxonomic classification
    system using exact k-mer matches to achieve high accuracy and fast classification
    speeds. This classifier matches each k-mer within a query sequence to the lowest
    common ancestor (LCA) of all genomes containing the given k-mer. The k-mer assignments
    inform the classification algorithm.

    Any assumption that Kraken’s raw read assignments can be directly translated into
    species or strain-level abundance estimates is flawed. Bracken (Bayesian Reestimation
    of Abundance after Classification with KrakEN), estimates species abundances in
    metagenomics samples by probabilistically re-distributing reads in the taxonomic
    tree. (Lu, Jennifer et al. “Bracken: estimating species abundance in metagenomics
    data.”)'
  documentation:
  - note: null
    type:
    - User manual
    url: https://github.com/DerrickWood/kraken2/wiki/Manual
  - note: Links to multiple Kraken 2 and bracken databases and indexes
    type:
    - User manual
    url: https://benlangmead.github.io/aws-indexes/k2
  download:
  - note: null
    type: Source code
    url: https://github.com/DerrickWood/kraken2/archive/v2.0.8-beta.tar.gz
    version: 2.0.8-beta
  editPermission:
    authors:
    - vashokan
    - Keiler_Collier
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: '`kraken2 --db <kraken2_database> <input.fastq>`'
    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: Taxonomic classification
      uri: http://edamontology.org/operation_3460
    output:
    - data:
        term: Taxonomy
        uri: http://edamontology.org/data_3028
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
  homepage: https://ccb.jhu.edu/software/kraken2/
  homepage_status: 0
  language:
  - C++
  - Perl
  lastUpdate: '2025-06-18T12:24:26.657325Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/DerrickWood/kraken2
  - note: null
    type:
    - Issue tracker
    url: https://github.com/DerrickWood/kraken2/issues
  maturity: null
  name: kraken2
  operatingSystem: []
  otherID: []
  owner: anand-anshu
  publication:
  - doi: 10.1101/762302
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation:
  - biotoolsID: kraken
    type: isNewVersionOf
  - biotoolsID: bracken
    type: usedBy
  toolType:
  - Command-line tool
  topic:
  - term: Taxonomy
    uri: http://edamontology.org/topic_0637
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  - term: Microbial ecology
    uri: http://edamontology.org/topic_3697
  - term: Microbiology
    uri: http://edamontology.org/topic_3301
  validated: 1
  version:
  - 2.0.8-beta
- accessibility: Open access
  additionDate: '2021-05-26T21:13:32Z'
  biotoolsCURIE: biotools:nextdenovo
  biotoolsID: nextdenovo
  collectionID:
  - ONTeater
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: support@nextomics.org
    fundrefid: null
    gridid: null
    name: Nextomics
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Primary contact
    url: null
  description: NextDenovo is a string graph-based de novo assembler for long reads
    (CLR, HiFi and ONT). It uses a "correct-then-assemble" strategy similar to canu
    (no correction step for PacBio Hifi reads), but requires significantly less computing
    resources and storages.
  documentation:
  - note: null
    type:
    - User manual
    url: https://nextdenovo.readthedocs.io/en/latest/
  download:
  - note: null
    type: Source code
    url: https://github.com/Nextomics/NextDenovo/releases/tag/2.5.2
    version: null
  editPermission:
    authors:
    - jw
    - ELIXIR-CZ
    - Keiler_Collier
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Sequence trace
        uri: http://edamontology.org/data_0924
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
      - term: FASTQ
        uri: http://edamontology.org/format_1930
    note: null
    operation:
    - term: De-novo assembly
      uri: http://edamontology.org/operation_0524
    - term: Genome assembly
      uri: http://edamontology.org/operation_0525
    output:
    - data:
        term: Sequence assembly
        uri: http://edamontology.org/data_0925
      format:
      - term: Sequence assembly format (text)
        uri: http://edamontology.org/format_2561
      - term: FASTA
        uri: http://edamontology.org/format_1929
  homepage: https://github.com/Nextomics/NextDenovo
  homepage_status: 0
  language:
  - Python
  - C
  lastUpdate: '2025-06-18T12:20:23.607241Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Issue tracker
    url: https://github.com/Nextomics/NextDenovo/issues
  maturity: Mature
  name: NextDenovo
  operatingSystem: []
  otherID: []
  owner: Kigaard
  publication:
  - doi: 10.1101/2023.03.09.531669.
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Sequencing
    uri: http://edamontology.org/topic_3168
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  validated: 0
  version:
  - v.2.5.2
- accessibility: Open access
  additionDate: '2021-05-27T09:04:45Z'
  biotoolsCURIE: biotools:quickmerge
  biotoolsID: quickmerge
  collectionID:
  - ONTeater
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Mahul Chakraborty
    note: null
    orcidid: https://orcid.org/0000-0003-2414-9187
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://mahulchakraborty.wordpress.com/
  description: Quickmerge is a program that uses complementary information from genomes
    assembled with long reads in order to improve contiguity, and works with assemblies
    derived from both Pacific Biosciences or Oxford Nanopore. Quickmerge will even
    work with hybrid assemblies made by combining long reads and Illumina short reads.
  documentation: []
  download: []
  editPermission:
    authors:
    - ELIXIR-CZ
    - Keiler_Collier
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: merge_wrapper.py -pre output_prefix assembly_1.fa assembly_2.fa
    input:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: 'Runs whole merge process on an input assembly.

      Assembly 2 will be used to fill gaps in assembly 1.'
    operation:
    - term: Genome assembly
      uri: http://edamontology.org/operation_0525
    - term: Scaffolding
      uri: http://edamontology.org/operation_3216
    - term: De-novo assembly
      uri: http://edamontology.org/operation_0524
    - term: Genotyping
      uri: http://edamontology.org/operation_3196
    output:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
  homepage: https://github.com/mahulchak/quickmerge
  homepage_status: 0
  language:
  - C++
  - C
  lastUpdate: '2025-06-18T12:17:20.983962Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Issue tracker
    url: https://github.com/mahulchak/quickmerge/issues
  - note: null
    type:
    - Repository
    url: https://github.com/mahulchak/quickmerge
  maturity: null
  name: quickmerge
  operatingSystem:
  - Mac
  - Linux
  otherID: []
  owner: Kigaard
  publication:
  - doi: 10.1534/g3.118.200162
    metadata:
      abstract: Accurate and comprehensive characterization of genetic variation is
        essential for deciphering the genetic basis of diseases and other phenotypes.
        A vast amount of genetic variation stems from largescale sequence changes
        arising from the duplication, deletion, inversion, and translocation of sequences.
        In the past 10 years, high-throughput short reads have greatly expanded our
        ability to assay sequence variation due to single nucleotide polymorphisms.
        However, a recent de novo assembly of a second Drosophila melanogaster reference
        genome has revealed that short read genotyping methods miss hundreds of structural
        variants, including those affecting phenotypes. While genomes assembled using
        highcoverage long reads can achieve high levels of contiguity and completeness,
        concerns about cost, errors, and low yield have limited widespread adoption
        of such sequencing approaches. Here we resequenced the reference strain of
        D. melanogaster (ISO1) on a single Oxford Nanopore MinION flow cell run for
        24 hr. Using only reads longer than 1 kb or with at least 30x coverage, we
        assembled a highly contiguous de novo genome. The addition of inexpensive
        paired reads and subsequent scaffolding using an optical map technology achieved
        an assembly with completeness and contiguity comparable to the D. melanogaster
        reference assembly. Comparison of our assembly to the reference assembly of
        ISO1 uncovered a number of structural variants (SVs), including novel LTR
        transposable element insertions and duplications affecting genes with developmental,
        behavioral, and metabolic functions. Collectively, these SVs provide a snapshot
        of the dynamics of genome evolution. Furthermore, our assembly and comparison
        to the D. melanogaster reference genome demonstrates that high-quality de
        novo assembly of reference genomes and comprehensive variant discovery using
        such assemblies are now possible by a single lab for under $1,000 (USD).
      authors:
      - name: Solares E.A.
      - name: Chakraborty M.
      - name: Miller D.E.
      - name: Kalsow S.
      - name: Hall K.
      - name: Perera A.G.
      - name: Emerson J.J.
      - name: Scott Hawley R.
      citationCount: 70
      date: '2018-10-01T00:00:00Z'
      journal: 'G3: Genes, Genomes, Genetics'
      title: Rapid low-cost assembly of the drosophila melanogaster reference genome
        using low-coverage, long-read sequencing
    note: null
    pmcid: PMC6169397
    pmid: '30018084'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Structural variation
    uri: http://edamontology.org/topic_3175
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  - term: DNA polymorphism
    uri: http://edamontology.org/topic_2885
  - term: Whole genome sequencing
    uri: http://edamontology.org/topic_3673
  - term: Genotype and phenotype
    uri: http://edamontology.org/topic_0625
  validated: 0
  version:
  - v.0.3
- accessibility: Open access
  additionDate: '2022-05-16T13:26:15.720803Z'
  biotoolsCURIE: biotools:skm
  biotoolsID: skm
  collectionID:
  - ELIXIR-SI
  - Plant Systems Biology
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: National Institute of Biology, Department of Biotechnology and Systems Biology
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: http://www.nib.si/
  - email: carissarobyn.bleker@nib.si
    fundrefid: null
    gridid: null
    name: Carissa Bleker
    note: null
    orcidid: https://orcid.org/0000-0003-1617-7145
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    - Maintainer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Kristina Gruden
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Živa Ramšak
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Vid Podpečan
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Developer
    url: null
  description: 'Stress Knowledge Map:  A compilation of knowledge on mechanisms underlying
    responses of plants to stress, the so called stress signalling network.'
  documentation:
  - note: null
    type:
    - General
    url: https://skm.nib.si/documentation
  download: []
  editPermission:
    authors:
    - zagor
    type: group
  elixirCommunity:
  - Plant Sciences
  elixirNode:
  - Slovenia
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Gene name
        uri: http://edamontology.org/data_2299
      format: []
    note: null
    operation:
    - term: Database search
      uri: http://edamontology.org/operation_2421
    output:
    - data:
        term: Database search results
        uri: http://edamontology.org/data_2080
      format:
      - term: JSON
        uri: http://edamontology.org/format_3464
      - term: sif
        uri: http://edamontology.org/format_3619
  - cmd: null
    input: []
    note: null
    operation:
    - term: Data retrieval
      uri: http://edamontology.org/operation_2422
    output:
    - data:
        term: Mathematical model
        uri: http://edamontology.org/data_0950
      format:
      - term: SBML
        uri: http://edamontology.org/format_2585
      - term: SBGN-ML
        uri: http://edamontology.org/format_3692
      - term: sif
        uri: http://edamontology.org/format_3619
  homepage: https://skm.nib.si/
  homepage_status: 0
  language: []
  lastUpdate: '2025-06-18T12:10:26.465410Z'
  license: null
  link:
  - note: null
    type:
    - Other
    url: https://skm.nib.si/contact
  maturity: Emerging
  name: SKM
  operatingSystem: []
  otherID: []
  owner: carissa
  publication:
  - doi: 10.1016/j.xplc.2024.100920
    metadata:
      abstract: 'Stress Knowledge Map (SKM; https://skm.nib.si) is a publicly available
        resource containing two complementary knowledge graphs that describe the current
        knowledge of biochemical, signaling, and regulatory molecular interactions
        in plants: a highly curated model of plant stress signaling (PSS; 543 reactions)
        and a large comprehensive knowledge network (488 390 interactions). Both were
        constructed by domain experts through systematic curation of diverse literature
        and database resources. SKM provides a single entry point for investigations
        of plant stress response and related growth trade-offs, as well as interactive
        explorations of current knowledge. PSS is also formulated as a qualitative
        and quantitative model for systems biology and thus represents a starting
        point for a plant digital twin. Here, we describe the features of SKM and
        show, through two case studies, how it can be used for complex analyses, including
        systematic hypothesis generation and design of validation experiments, or
        to gain new insights into experimental observations in plant biology.'
      authors:
      - name: Bleker C.
      - name: Ramsak
      - name: Bittner A.
      - name: Podpecan V.
      - name: Zagorscak M.
      - name: Wurzinger B.
      - name: Baebler
      - name: Petek M.
      - name: Kriznik M.
      - name: van Dieren A.
      - name: Gruber J.
      - name: Afjehi-Sadat L.
      - name: Weckwerth W.
      - name: Zupanic A.
      - name: Teige M.
      - name: Vothknecht U.C.
      - name: Gruden K.
      citationCount: 8
      date: '2024-06-10T00:00:00Z'
      journal: Plant Communications
      title: 'Stress Knowledge Map: A knowledge graph resource for systems biology
        analysis of plant stress responses'
    note: 'Stress Knowledge Map: A knowledge graph resource for systems biology analysis
      of plant stress responses'
    pmcid: null
    pmid: '38616489'
    type:
    - Primary
    version: null
  relation:
  - biotoolsID: gomapman
    type: uses
  - biotoolsID: newt-ve
    type: uses
  toolType:
  - Web application
  - Database portal
  topic:
  - term: Systems biology
    uri: http://edamontology.org/topic_2259
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  - term: Plant biology
    uri: http://edamontology.org/topic_0780
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2017-01-13T13:16:01Z'
  biotoolsCURIE: biotools:quast
  biotoolsID: quast
  collectionID:
  - ONTeater
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: quast.support@cab.spbu.ru
    fundrefid: null
    gridid: null
    name: QUAST Support
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: "QUAST stands for QUality ASsessment Tool.  \nIt evaluates a quality\
    \ of genome assemblies by computing various metrics and providing nice reports."
  documentation:
  - note: null
    type:
    - General
    url: http://quast.bioinf.spbau.ru/
  download: []
  editPermission:
    authors:
    - ELIXIR-CZ
    - Keiler_Collier
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: quast -ek assembly.fa --out output_prefix
    input:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: '# Running quast on a eukaryotic genome'
    operation:
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    - term: Sequence assembly validation
      uri: http://edamontology.org/operation_3180
    output: []
  homepage: http://quast.sourceforge.net/quast
  homepage_status: 0
  language:
  - Perl
  - Python
  - C
  lastUpdate: '2025-06-18T11:53:52.861712Z'
  license: GPL-2.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/ablab/quast
  - note: null
    type:
    - Issue tracker
    url: https://github.com/ablab/quast/issues
  maturity: Mature
  name: QUAST
  operatingSystem:
  - Linux
  - Mac
  otherID: []
  owner: seqwiki_import
  publication:
  - doi: 10.1093/bioinformatics/btt086
    metadata:
      abstract: Limitations of genome sequencing techniques have led to dozens of
        assembly algorithms, none of which is perfect. A number of methods for comparing
        assemblers have been developed, but none is yet a recognized benchmark. Further,
        most existing methods for comparing assemblies are only applicable to new
        assemblies of finished genomes; the problem of evaluating assemblies of previously
        unsequenced species has not been adequately considered. Here, we present QUAST
        - a quality assessment tool for evaluating and comparing genome assemblies.
        This tool improves on leading assembly comparison software with new ideas
        and quality metrics. QUAST can evaluate assemblies both with a reference genome,
        as well as without a reference. QUAST produces many reports, summary tables
        and plots to help scientists in their research and in their publications.
        In this study, we used QUAST to compare several genome assemblers on three
        datasets. QUAST tables and plots for all of them are available in the Supplementary
        Material, and interactive versions of these reports are on the QUAST website.
        © 2013 The Author.
      authors:
      - name: Gurevich A.
      - name: Saveliev V.
      - name: Vyahhi N.
      - name: Tesler G.
      citationCount: 6872
      date: '2013-04-15T00:00:00Z'
      journal: Bioinformatics
      title: 'QUAST: Quality assessment tool for genome assemblies'
    note: null
    pmcid: PMC3624806
    pmid: '23422339'
    type: []
    version: null
  relation: []
  toolType:
  - Workflow
  topic:
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  validated: 1
  version:
  - v.5.3.0
- accessibility: Open access
  additionDate: '2019-11-14T18:44:38Z'
  biotoolsCURIE: biotools:Racon
  biotoolsID: Racon
  collectionID:
  - ONTeater
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: cskang@korea.kr
    fundrefid: null
    gridid: null
    name: Chon-Sik Kang
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: changsookim@cnu.ac.kr
    fundrefid: null
    gridid: null
    name: Changsoo Kim
    note: null
    orcidid: https://orcid.org/0000-0002-3596-2934
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: 'Consensus module for raw de novo DNA assembly of long uncorrected
    reads


    Racon is intended as a standalone consensus module to correct raw contigs generated
    by rapid assembly methods which do not include a consensus step. The goal of Racon
    is to generate genomic consensus which is of similar or better quality compared
    to the output generated by assembly methods which employ both error correction
    and consensus steps, while providing a speedup of several times compared to those
    methods. It supports data produced by both Pacific Biosciences and Oxford Nanopore
    Technologies.'
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: racon -u reads.fa mapped_reads.sam assembly.fa > assembly_racon.fa
    input:
    - data:
        term: Nucleic acid sequence alignment
        uri: http://edamontology.org/data_1383
      format:
      - term: BAM
        uri: http://edamontology.org/format_2572
      - term: SAM
        uri: http://edamontology.org/format_2573
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: '# The mapping file can be generated with any mapping program - eg, bwa-mem
      or minimap2.

      # The following is an example using minimap2 with ONT data

      minimap2 assembly.fa-ax map-ont reads.fa > mapped_reads.sam'
    operation:
    - term: Genome assembly
      uri: http://edamontology.org/operation_0525
    - term: Mapping assembly
      uri: http://edamontology.org/operation_0523
    output:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
  homepage: https://github.com/isovic/racon
  homepage_status: 0
  language:
  - C++
  - Python
  lastUpdate: '2025-06-18T11:42:42.378216Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/isovic/racon
  - note: null
    type:
    - Issue tracker
    url: https://github.com/isovic/racon/issues
  maturity: null
  name: Racon
  operatingSystem:
  - Mac
  - Linux
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.3390/plants8080270
    metadata:
      abstract: 'The whole genome sequencing (WGS) has become a crucial tool in understanding
        genome structure and genetic variation. The MinION sequencing of Oxford Nanopore
        Technologies (ONT) is an excellent approach for performing WGS and it has
        advantages in comparison with other Next-Generation Sequencing (NGS): It is
        relatively inexpensive, portable, has simple library preparation, can be monitored
        in real-time, and has no theoretical limits on reading length. Sorghum bicolor
        (L.) Moench is diploid (2n = 2x = 20) with a genome size of about 730 Mb,
        and its genome sequence information is released in the Phytozome database.
        Therefore, sorghum can be used as a good reference. However, plant species
        have complex and large genomes when compared to animals or microorganisms.
        As a result, complete genome sequencing is difficult for plant species. MinION
        sequencing that produces long-reads can be an excellent tool for overcoming
        the weak assembly of short-reads generated from NGS by minimizing the generation
        of gaps or covering the repetitive sequence that appears on the plant genome.
        Here, we conducted the genome sequencing for S. bicolor cv. BTx623 while using
        the MinION platform and obtained 895,678 reads and 17.9 gigabytes (Gb) (ca.
        25× coverage of reference) from long-read sequence data. A total of 6124 contigs
        (covering 45.9%) were generated from Canu, and a total of 2661 contigs (covering
        50%) were generated from Minimap and Miniasm with a Racon through a de novo
        assembly using two different tools and mapped assembled contigs against the
        sorghum reference genome. Our results provide an optimal series of long-read
        sequencing analysis for plant species while using the MinION platform and
        a clue to determine the total sequencing scale for optimal coverage that is
        based on various genome sizes.'
      authors:
      - name: Lee Y.G.
      - name: Choi S.C.
      - name: Kang Y.
      - name: Kim K.M.
      - name: Kang C.-S.
      - name: Kim C.
      citationCount: 13
      date: '2019-08-01T00:00:00Z'
      journal: Plants
      title: 'Constructing a reference genome in a single lab: The possibility to
        use oxford nanopore technology'
    note: null
    pmcid: PMC6724115
    pmid: '31390788'
    type: []
    version: null
  relation: []
  toolType: []
  topic:
  - term: Whole genome sequencing
    uri: http://edamontology.org/topic_3673
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2019-11-14T20:08:20Z'
  biotoolsCURIE: biotools:Flye
  biotoolsID: Flye
  collectionID:
  - ONTeater
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: fenderglass@gmail.com
    fundrefid: null
    gridid: null
    name: Mikhail Kolmogorov
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    - Support
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Yu Lin
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Jeffrey Yuan
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  description: 'Flye is a de novo assembler for single molecule sequencing reads,
    such as those produced by PacBio and Oxford Nanopore Technologies. It is designed
    for a wide range of datasets, from small bacterial projects to large mammalian-scale
    assemblies. The package represents a complete pipeline: it takes raw PB / ONT
    reads as input and outputs polished contigs.'
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
    note: null
    operation:
    - term: Genome assembly
      uri: http://edamontology.org/operation_0525
    - term: De-novo assembly
      uri: http://edamontology.org/operation_0524
    - term: Mapping assembly
      uri: http://edamontology.org/operation_0523
    - term: Cross-assembly
      uri: http://edamontology.org/operation_3730
    output:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
  homepage: https://github.com/fenderglass/Flye
  homepage_status: 0
  language:
  - C++
  - Python
  - C
  lastUpdate: '2025-06-18T10:20:03.775603Z'
  license: BSD-3-Clause
  link:
  - note: null
    type:
    - Issue tracker
    url: https://github.com/fenderglass/Flye/issues
  - note: null
    type:
    - Repository
    url: https://github.com/mikolmogorov/Flye
  maturity: null
  name: Flye
  operatingSystem:
  - Mac
  - Linux
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1099/mgen.0.000294
    metadata:
      abstract: Illumina sequencing allows rapid, cheap and accurate whole genome
        bacterial analyses, but short reads (<300 bp) do not usually enable complete
        genome assembly. Long-read sequencing greatly assists with resolving complex
        bacterial genomes, particularly when combined with short-read Illumina data
        (hybrid assembly). However, it is not clear how different long-read sequencing
        methods affect hybrid assembly accuracy. Relative automation of the assembly
        process is also crucial to facilitating high-throughput complete bacterial
        genome reconstruction, avoiding multiple bespoke filtering and data manipulation
        steps. In this study, we compared hybrid assemblies for 20 bacterial isolates,
        including two reference strains, using Illumina sequencing and long reads
        from either Oxford Nanopore Technologies (ONT) or SMRT Pacific Biosciences
        (PacBio) sequencing platforms. We chose isolates from the family Enterobacteriaceae,
        as these frequently have highly plastic, repetitive genetic structures, and
        complete genome reconstruction for these species is relevant for a precise
        understanding of the epidemiology of antimicrobial resistance. We de novo
        assembled genomes using the hybrid assembler Unicycler and compared different
        read processing strategies, as well as comparing to long-read-only assembly
        with Flye followed by short-read polishing with Pilon. Hybrid assembly with
        either PacBio or ONT reads facilitated high-quality genome reconstruction,
        and was superior to the longread assembly and polishing approach evaluated
        with respect to accuracy and completeness. Combining ONT and Illumina reads
        fully resolved most genomes without additional manual steps, and at a lower
        consumables cost per isolate in our setting. Automated hybrid assembly is
        a powerful tool for complete and accurate bacterial genome assembly.
      authors:
      - name: De Maio N.
      - name: Shaw L.P.
      - name: Hubbard A.
      - name: George S.
      - name: Sanderson N.D.
      - name: Swann J.
      - name: Wick R.
      - name: Oun M.A.
      - name: Stubberfield E.
      - name: Hoosdally S.J.
      - name: Crook D.W.
      - name: Peto T.E.A.
      - name: Sheppard A.E.
      - name: Bailey M.J.
      - name: Read D.S.
      - name: Anjum M.F.
      - name: Sarah Walker A.
      - name: Stoesser N.
      citationCount: 166
      date: '2019-01-01T00:00:00Z'
      journal: Microbial Genomics
      title: Comparison of long-read sequencing technologies in the hybrid assembly
        of complex bacterial genomes
    note: null
    pmcid: PMC6807382
    pmid: '31483244'
    type:
    - Usage
    version: null
  - doi: 10.1038/s41587-019-0072-8
    metadata:
      abstract: Accurate genome assembly is hampered by repetitive regions. Although
        long single molecule sequencing reads are better able to resolve genomic repeats
        than short-read data, most long-read assembly algorithms do not provide the
        repeat characterization necessary for producing optimal assemblies. Here,
        we present Flye, a long-read assembly algorithm that generates arbitrary paths
        in an unknown repeat graph, called disjointigs, and constructs an accurate
        repeat graph from these error-riddled disjointigs. We benchmark Flye against
        five state-of-the-art assemblers and show that it generates better or comparable
        assemblies, while being an order of magnitude faster. Flye nearly doubled
        the contiguity of the human genome assembly (as measured by the NGA50 assembly
        quality metric) compared with existing assemblers.
      authors:
      - name: Kolmogorov M.
      - name: Yuan J.
      - name: Lin Y.
      - name: Pevzner P.A.
      citationCount: 3077
      date: '2019-05-01T00:00:00Z'
      journal: Nature Biotechnology
      title: Assembly of long, error-prone reads using repeat graphs
    note: null
    pmcid: null
    pmid: '30936562'
    type:
    - Primary
    version: null
  - doi: 10.1038/s41592-020-00971-x
    metadata:
      abstract: Long-read sequencing technologies have substantially improved the
        assemblies of many isolate bacterial genomes as compared to fragmented short-read
        assemblies. However, assembling complex metagenomic datasets remains difficult
        even for state-of-the-art long-read assemblers. Here we present metaFlye,
        which addresses important long-read metagenomic assembly challenges, such
        as uneven bacterial composition and intra-species heterogeneity. First, we
        benchmarked metaFlye using simulated and mock bacterial communities and show
        that it consistently produces assemblies with better completeness and contiguity
        than state-of-the-art long-read assemblers. Second, we performed long-read
        sequencing of the sheep microbiome and applied metaFlye to reconstruct 63
        complete or nearly complete bacterial genomes within single contigs. Finally,
        we show that long-read assembly of human microbiomes enables the discovery
        of full-length biosynthetic gene clusters that encode biomedically important
        natural products.
      authors:
      - name: Kolmogorov M.
      - name: Bickhart D.M.
      - name: Behsaz B.
      - name: Gurevich A.
      - name: Rayko M.
      - name: Shin S.B.
      - name: Kuhn K.
      - name: Yuan J.
      - name: Polevikov E.
      - name: Smith T.P.L.
      - name: Pevzner P.A.
      citationCount: 511
      date: '2020-11-01T00:00:00Z'
      journal: Nature Methods
      title: 'metaFlye: scalable long-read metagenome assembly using repeat graphs'
    note: null
    pmcid: PMC10699202
    pmid: '33020656'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  - Workflow
  topic:
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  - term: Whole genome sequencing
    uri: http://edamontology.org/topic_3673
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  validated: 1
  version:
  - 2.9.6
- accessibility: Open access
  additionDate: '2025-06-16T09:48:41.534811Z'
  biotoolsCURIE: biotools:barcode_of_life_database
  biotoolsID: barcode_of_life_database
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: 'An interactive gateway designed for the tracking and dissemination
    of DNA barcode reference data. The most commonly used marker is a region of the
    cytochrome c oxidase I (COI) gene found in mitochondria but multiple other are
    used for plants and fungi.

    Supported markers:  COI, ITS, rbcL, matK and 18S.'
  documentation: []
  download: []
  editPermission:
    authors:
    - Keiler_Collier
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: DNA sequence
        uri: http://edamontology.org/data_3494
      format: []
    - data:
        term: Geographic location
        uri: http://edamontology.org/data_3720
      format: []
    note: null
    operation:
    - term: Sequence database search
      uri: http://edamontology.org/operation_0338
    output:
    - data:
        term: Taxon
        uri: http://edamontology.org/data_1868
      format: []
    - data:
        term: Geographic location
        uri: http://edamontology.org/data_3720
      format: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Map drawing
      uri: http://edamontology.org/operation_0573
    output: []
  homepage: https://boldsystems.org/
  homepage_status: 0
  language: []
  lastUpdate: '2025-06-17T16:32:35.017034Z'
  license: null
  link: []
  maturity: Mature
  name: BOLD (Barcode of Life Database)
  operatingSystem: []
  otherID: []
  owner: adriaan
  publication: []
  relation: []
  toolType:
  - Database portal
  - Web API
  topic:
  - term: Biodiversity
    uri: http://edamontology.org/topic_3050
  - term: Metabarcoding
    uri: http://edamontology.org/topic_4038
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2020-06-18T05:28:02Z'
  biotoolsCURIE: biotools:biosimulations
  biotoolsID: biosimulations
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: karr@mssm.edu
    fundrefid: null
    gridid: null
    name: Jonathan Karr
    note: null
    orcidid: https://orcid.org/0000-0002-2605-5080
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: https://www.karrlab.org
  - email: null
    fundrefid: null
    gridid: null
    name: Bilal Shaikh
    note: null
    orcidid: https://orcid.org/0000-0001-5801-5510
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  description: BioSimulations is a web application for sharing and re-using biomodels,
    simulations, and visualizations of simulations results. BioSimulations supports
    a wide range of modeling frameworks (e.g., kinetic, constraint-based, and logical
    modeling), model formats (e.g., BNGL, CellML, SBML), and simulation tools (e.g.,
    COPASI, libRoadRunner/tellurium, NFSim, VCell). BioSimulations aims to help researchers
    discover published models that might be useful for their research and quickly
    try them via a simple web-based interface.
  documentation:
  - note: null
    type:
    - General
    url: https://docs.biosimulations.org
  - note: null
    type:
    - API documentation
    url: https://api.biosimulations.org/
  - note: null
    type:
    - Code of conduct
    url: https://docs.biosimulations.org/developers/conduct/
  - note: null
    type:
    - Terms of use
    url: https://docs.biosimulations.org/about/terms/
  download: []
  editPermission:
    authors:
    - bilalshaikh42
    - Bioinfo
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Mathematical model
        uri: http://edamontology.org/data_0950
      format:
      - term: SBML
        uri: http://edamontology.org/format_2585
      - term: CellML
        uri: http://edamontology.org/format_3240
    note: null
    operation:
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    - term: Modelling and simulation
      uri: http://edamontology.org/operation_2426
    output:
    - data:
        term: Trajectory data
        uri: http://edamontology.org/data_3870
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
      - term: SVG
        uri: http://edamontology.org/format_3604
  homepage: https://www.biosimulations.org/
  homepage_status: 0
  language:
  - JavaScript
  - Python
  lastUpdate: '2025-06-17T16:32:28.548746Z'
  license: MIT
  link:
  - note: null
    type:
    - Issue tracker
    url: https://github.com/reproducible-biomedical-modeling/Biosimulations/issues
  - note: null
    type:
    - Repository
    url: https://github.com/reproducible-biomedical-modeling/Biosimulations
  - note: null
    type:
    - Service
    url: https://api.biosimulations.org/
  maturity: Emerging
  name: BioSimulations
  operatingSystem: []
  otherID:
  - type: rrid
    value: RRID:SCR_018733
    version: null
  owner: Bioinfo
  publication: []
  relation:
  - biotoolsID: runbiosimulations
    type: uses
  - biotoolsID: biosimulators
    type: uses
  - biotoolsID: biomodels
    type: uses
  - biotoolsID: sbml
    type: uses
  - biotoolsID: bionetgen
    type: uses
  - biotoolsID: cobrapy
    type: uses
  - biotoolsID: copasi
    type: uses
  - biotoolsID: libroadrunner
    type: uses
  toolType:
  - Command-line tool
  - Web API
  - Web application
  - Web service
  topic:
  - term: Systems biology
    uri: http://edamontology.org/topic_2259
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2025-06-17T15:24:06.806811Z'
  biotoolsCURIE: biotools:b10k
  biotoolsID: b10k
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: The Bird 10,000 Genomes (B10K) Project is an initiative to generate
    representative draft genome sequences from all extant bird species. The project
    aims to reconstruct the tree of life with full genome data, reveal the genomic
    basis of global bird diversity, and assess the impact of environmental change
    on diversity.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
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  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: DNA sequence
        uri: http://edamontology.org/data_3494
      format: []
    note: null
    operation:
    - term: Sequence database search
      uri: http://edamontology.org/operation_0338
    output:
    - data:
        term: Taxon
        uri: http://edamontology.org/data_1868
      format: []
  homepage: https://b10k.com/
  homepage_status: 0
  language: []
  lastUpdate: '2025-06-17T15:25:02.609832Z'
  license: null
  link: []
  maturity: Emerging
  name: Bird 10,000 Genomes (B10K)
  operatingSystem: []
  otherID: []
  owner: adriaan
  publication: []
  relation: []
  toolType:
  - Database portal
  topic:
  - term: Biodiversity
    uri: http://edamontology.org/topic_3050
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2017-08-20T16:34:27Z'
  biotoolsCURIE: biotools:pavian
  biotoolsID: pavian
  collectionID:
  - Animal and Crop Genomics
  - Biodiversity
  - microbiome
  confidence_flag: null
  cost: null
  credit:
  - email: fbreitw1@jhmi.edu
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Web application for exploring metagenomics classification results,
    with a special focus on infectious disease diagnosis. Pinpointing pathogens in
    metagenomics classification results is often complicated by host and laboratory
    contaminants as well as many non-pathogenic microbiota. Researchers can analyze,
    display and transform results from the Kraken and Centrifuge classifiers using
    interactive tables, heatmaps and flow diagrams.
  documentation:
  - note: null
    type:
    - User manual
    url: https://ccb.jhu.edu/software/pavian/index.shtml?t=manual
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Taxonomy
        uri: http://edamontology.org/data_3028
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
    note: null
    operation:
    - term: Annotation
      uri: http://edamontology.org/operation_0226
    - term: Taxonomic classification
      uri: http://edamontology.org/operation_3460
    output:
    - data:
        term: Plot
        uri: http://edamontology.org/data_2884
      format: []
  homepage: https://ccb.jhu.edu/software/pavian/
  homepage_status: 0
  language:
  - R
  lastUpdate: '2025-06-17T15:12:54.095225Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/fbreitwieser/pavian/tree/master
  maturity: null
  name: Pavian
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: admin
  publication:
  - doi: 10.1101/084715
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Web application
  - Command-line tool
  topic:
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  - term: Model organisms
    uri: http://edamontology.org/topic_0621
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2017-01-17T15:04:54Z'
  biotoolsCURIE: biotools:xcms
  biotoolsID: xcms
  collectionID:
  - BioConductor
  - Bioconda
  - Galaxy Tools
  confidence_flag: null
  cost: null
  credit:
  - email: sneumann@ipb-halle.de
    fundrefid: null
    gridid: null
    name: Steffen Neumann
    note: null
    orcidid: https://orcid.org/0000-0002-7899-7192
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Framework for processing and visualization of chromatographically separated
    and single-spectra mass spectral data.  The packages enables imports from AIA/ANDI
    NetCDF, mzXML, mzData and mzML files and preprocesses data for high-throughput,
    untargeted analyte profiling.
  documentation:
  - note: null
    type:
    - User manual
    url: http://bioconductor.org/packages/release/bioc/html/xcms.html
  - note: Galaxy training material for LC-MS data preprocessing with XCMS
    type:
    - Training material
    url: https://training.galaxyproject.org/training-material/topics/metabolomics/tutorials/lcms-preprocessing/tutorial.html
  - note: Galaxy training for GC-MS data preprocessing with XCMS
    type:
    - Training material
    url: https://training.galaxyproject.org/training-material/topics/metabolomics/tutorials/gc_ms_with_xcms/tutorial.html
  - note: Tutorial on using the XCMS R library
    type:
    - Training material
    url: https://jorainer.github.io/xcmsTutorials/
  download:
  - note: null
    type: Source code
    url: http://bioconductor/packages/release/bioc/src/contrib/xcms_1.50.1.tar.gz
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  - note: null
    type:
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    - Galaxy service
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        spectrometry experiments. Some manufacturers employ a mass calibration system
        that regularly switches between the analyte and a standard reference compound,
        and leads to gaps in the analyte data. We present a method for correction
        of such gaps in global molecular profiling applications such as metabolomics.
        We demonstrate that it improves peak detection and quantification, successfully
        recovering the expected number of peaks and intensity distribution in an example
        metabolomics dataset. © The Author 2010. Published by Oxford University Press.
        All rights reserved.'
      authors:
      - name: Benton H.P.
      - name: Want E.J.
      - name: Ebbels T.M.D.
      citationCount: 159
      date: '2010-07-29T00:00:00Z'
      journal: Bioinformatics
      title: Correction of mass calibration gaps in liquid chromatography-mass spectrometry
        metabolomics data
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  license: CC-BY-NC-3.0
  link:
  - note: References used in developing MitoFish
    type:
    - Other
    url: https://mitofish.aori.u-tokyo.ac.jp/about/refs/
  - note: Sample input and output
    type:
    - Other
    url: https://mitofish.aori.u-tokyo.ac.jp/species/detail/?genus=Anguilla&species=japonica
  - note: GitHub Repo of the MiFish and MitoAnnotator pipelines
    type:
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    url: https://github.com/tao-bioinfo/MiFish
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  name: MitoAnnotator
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  confidence_flag: null
  cost: Free of charge
  credit: []
  description: eBird gathers knowledge from birdwatchers in the form of checklists
    of birds, maps, audio recordings .
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  function:
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    note: null
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    note: null
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  function:
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    note: null
    operation:
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    - data:
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    - data:
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  link: []
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  name: Zoonomia
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  validated: 0
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- accessibility: Open access
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  biotoolsCURIE: biotools:dnazoo
  biotoolsID: dnazoo
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  cost: Free of charge
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  description: DNA Zoo data includes genome assemblies, genome annotations, DNA-Seq
    data, and Hi-C maps.
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  function:
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    input:
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    note: null
    operation:
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      format: []
    - data:
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  license: null
  link: []
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  biotoolsCURIE: biotools:arctosdb
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  confidence_flag: null
  cost: Free of charge
  credit: []
  description: Arctos is both a community and an online museum collection management
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    It provides fundamental research infrastructure and is intended for curators,
    collection managers, investigators, educators, and anyone interested in natural
    and cultural history.
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  function:
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    input:
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    note: null
    operation:
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    output:
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      format: []
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  link: []
  maturity: Mature
  name: ARCTOS
  operatingSystem: []
  otherID: []
  owner: adriaan
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  topic:
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    uri: http://edamontology.org/topic_3050
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2025-06-16T12:07:16.055880Z'
  biotoolsCURIE: biotools:barcode_of_life_cli
  biotoolsID: barcode_of_life_cli
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: A command line interface for data retrieval from the barcode of life
    data system.
  documentation: []
  download: []
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  function:
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    input:
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      format: []
    - data:
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    note: null
    operation:
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      format: []
    - data:
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    input: []
    note: null
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  language: []
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  license: null
  link: []
  maturity: Mature
  name: BOLD CLI
  operatingSystem: []
  otherID: []
  owner: adriaan
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  relation: []
  toolType:
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  topic:
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    uri: http://edamontology.org/topic_3050
  - term: Metabarcoding
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  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2025-06-15T04:45:08.927267Z'
  biotoolsCURIE: biotools:genomics_2_proteins_portal
  biotoolsID: genomics_2_proteins_portal
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: Genomics 2 Proteins (G2P) is a browser-based portal that lets you paste
    or upload variants and instantly map them onto PDB or AlphaFold structures. The
    viewer overlays UniProt domains, PTMs, disorder, conservation, and public variant
    tracks such as ClinVar, gnomAD, and HGMD, highlights 3-D hotspots, and can export
    a combined TSV or PyMOL session. Everything runs in the browser with no installation
    required, and a REST API is available for batch use.
  documentation: []
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  function:
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    input: []
    note: null
    operation:
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    - term: Structure visualisation
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      uri: http://edamontology.org/operation_0564
    - term: Sequence annotation
      uri: http://edamontology.org/operation_0361
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  homepage_status: 0
  language: []
  lastUpdate: '2025-06-15T04:51:27.735002Z'
  license: null
  link: []
  maturity: null
  name: Genomics 2 Proteins portal
  operatingSystem: []
  otherID: []
  owner: unethical
  publication:
  - doi: 10.1038/s41592-024-02409-0
    metadata:
      abstract: 'Recent advances in AI-based methods have revolutionized the field
        of structural biology. Concomitantly, high-throughput sequencing and functional
        genomics have generated genetic variants at an unprecedented scale. However,
        efficient tools and resources are needed to link disparate data types—to ‘map’
        variants onto protein structures, to better understand how the variation causes
        disease, and thereby design therapeutics. Here we present the Genomics 2 Proteins
        portal (https://g2p.broadinstitute.org/): a human proteome-wide resource that
        maps 20,076,998 genetic variants onto 42,413 protein sequences and 77,923
        structures, with a comprehensive set of structural and functional features.
        Additionally, the Genomics 2 Proteins portal allows users to interactively
        upload protein residue-wise annotations (for example, variants and scores)
        as well as the protein structure beyond databases to establish the connection
        between genomics to proteins. The portal serves as an easy-to-use discovery
        tool for researchers and scientists to hypothesize the structure–function
        relationship between natural or synthetic variations and their molecular phenotypes.'
      authors:
      - name: Kwon S.
      - name: Safer J.
      - name: Nguyen D.T.
      - name: Hoksza D.
      - name: May P.
      - name: Arbesfeld J.A.
      - name: Rubin A.F.
      - name: Campbell A.J.
      - name: Burgin A.
      - name: Iqbal S.
      citationCount: 1
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      journal: Nature Methods
      title: 'Genomics 2 Proteins portal: a resource and discovery tool for linking
        genetic screening outputs to protein sequences and structures'
    note: null
    pmcid: null
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    type: []
    version: null
  relation: []
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  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2025-06-12T11:47:48.641345Z'
  biotoolsCURIE: biotools:mzspeclib
  biotoolsID: mzspeclib
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  confidence_flag: tool
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  credit: []
  description: A python reference implementation of the mzSpecLib spectral library
    format.
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  - note: null
    type:
    - API documentation
    url: https://hupo-psi.github.io/mzSpecLib/
  download:
  - note: null
    type: Source code
    url: https://github.com/HUPO-PSI/mzspeclib-py
    version: null
  - note: null
    type: Software package
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    version: null
  editPermission:
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  elixirCommunity:
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  - Metabolomics
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  elixirPlatform:
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  function:
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        uri: http://edamontology.org/format_4039
      - term: MGF
        uri: http://edamontology.org/format_3651
    note: null
    operation:
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    output:
    - data:
        term: Mass spectrum
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      format: []
  - cmd: null
    input:
    - data:
        term: Mass spectrum
        uri: http://edamontology.org/data_0943
      format: []
    note: null
    operation:
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    output:
    - data:
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      format: []
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  language:
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  lastUpdate: '2025-06-12T11:57:26.484553Z'
  license: APSL-2.0
  link:
  - note: null
    type:
    - Discussion forum
    url: https://www.psidev.info/
  - note: null
    type:
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  name: mzspeclib
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  publication:
  - doi: 10.1021/acs.analchem.4c04091
    metadata:
      abstract: Mass spectral libraries are collections of reference spectra, usually
        associated with specific analytes from which the spectra were generated, that
        are used for further downstream analysis of new spectra. There are many different
        formats used for encoding spectral libraries, but none have undergone a standardization
        process to ensure broad applicability to many applications. As part of the
        Human Proteome Organization Proteomics Standards Initiative (PSI), we have
        developed a standardized format for encoding spectral libraries, called mzSpecLib
        (https://psidev.info/mzSpecLib). It is primarily a data model that flexibly
        encodes metadata about the library entries using the extensible PSI-MS controlled
        vocabulary and can be encoded in and converted between different serialization
        formats. We have also developed a standardized data model and serialization
        for fragment ion peak annotations, called mzPAF (https://psidev.info/mzPAF).
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        besides spectral libraries. The mzSpecLib and mzPAF standards are compatible
        with existing PSI standards such as ProForma 2.0 and the Universal Spectrum
        Identifier. The mzSpecLib and mzPAF standards have been primarily defined
        for peptides in proteomics applications with basic small molecule support.
        They could be extended in the future to other fields that need to encode spectral
        libraries for nonpeptidic analytes.
      authors:
      - name: Klein J.
      - name: Lam H.
      - name: Mak T.D.
      - name: Bittremieux W.
      - name: Perez-Riverol Y.
      - name: Gabriels R.
      - name: Shofstahl J.
      - name: Hecht H.
      - name: Binz P.-A.
      - name: Kawano S.
      - name: Van Den Bossche T.
      - name: Carver J.
      - name: Neely B.A.
      - name: Mendoza L.
      - name: Suomi T.
      - name: Claeys T.
      - name: Payne T.
      - name: Schulte D.
      - name: Sun Z.
      - name: Hoffmann N.
      - name: Zhu Y.
      - name: Neumann S.
      - name: Jones A.R.
      - name: Bandeira N.
      - name: Vizcaino J.A.
      - name: Deutsch E.W.
      citationCount: 1
      date: '2024-11-19T00:00:00Z'
      journal: Analytical Chemistry
      title: 'The Proteomics Standards Initiative Standardized Formats for Spectral
        Libraries and Fragment Ion Peak Annotations: mzSpecLib and mzPAF'
    note: null
    pmcid: null
    pmid: null
    type:
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    version: null
  relation: []
  toolType:
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  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  validated: 0
  version:
  - 1.0.5
- accessibility: Open access
  additionDate: '2023-06-14T13:47:49.064543Z'
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  biotoolsID: virtual_imaging_platform
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  cost: Free of charge
  credit: []
  description: VIP is a web portal for medical imaging applications. It allows users
    to access scientific applications as a service (directly through the web browser
    with no installation required), as well as distributed computing resources in
    a transparent manner. It exploits the resources available in the biomed virtual
    organization of the EGI e-infrastructure to offer an open service to researchers
    worldwide.
  documentation:
  - note: null
    type:
    - Other
    url: https://github.com/virtual-imaging-platform/VIP-portal/wiki
  download:
  - note: null
    type: Source code
    url: https://github.com/virtual-imaging-platform/
    version: 3.0.1
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        term: Image
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      format:
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        uri: http://edamontology.org/format_2333
    note: null
    operation:
    - term: Image analysis
      uri: http://edamontology.org/operation_3443
    output: []
  homepage: https://vip.creatis.insa-lyon.fr
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2025-06-06T11:51:24.125664Z'
  license: CECILL-B
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    url: https://vip.creatis.insa-lyon.fr/
  maturity: Mature
  name: Virtual Imaging Platform
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  owner: sorina.pop
  publication:
  - doi: 10.1109/tmi.2012.2220154
    metadata:
      abstract: This paper presents the Virtual Imaging Platform (VIP), a platform
        accessible at http://vip.creatis.insa-lyon.fr to facilitate the sharing of
        object models and medical image simulators, and to provide access to distributed
        computing and storage resources. A complete overview is presented, describing
        the ontologies designed to share models in a common repository, the workflow
        template used to integrate simulators, and the tools and strategies used to
        exploit computing and storage resources. Simulation results obtained in four
        image modalities and with different models show that VIP is versatile and
        robust enough to support large simulations. The platform currently has 200
        registered users who consumed 33 years of CPU time in 2011. © 1982-2012 IEEE.
      authors:
      - name: Glatard T.
      - name: Lartizien C.
      - name: Gibaud B.
      - name: Da Silva R.F.
      - name: Forestier G.
      - name: Cervenansky F.
      - name: Alessandrini M.
      - name: Benoit-Cattin H.
      - name: Bernard O.
      - name: Camarasu-Pop S.
      - name: Cerezo N.
      - name: Clarysse P.
      - name: Gaignard A.
      - name: Hugonnard P.
      - name: Liebgott H.
      - name: Marache S.
      - name: Marion A.
      - name: Montagnat J.
      - name: Tabary J.
      - name: Friboulet D.
      citationCount: 88
      date: '2013-01-10T00:00:00Z'
      journal: IEEE Transactions on Medical Imaging
      title: A virtual imaging platform for multi-modality medical image simulation
    note: null
    pmcid: null
    pmid: '23014715'
    type: []
    version: null
  relation: []
  toolType:
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  topic: []
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    fundrefid: null
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    name: Sebastian Gibb
    note: null
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    url: null
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    fundrefid: null
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    name: Korbinian Strimmer
    note: null
    orcidid: https://orcid.org/0000-0001-7917-2056
    rorid: null
    typeEntity: Person
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    url: null
  description: MALDIquant is a complete analysis pipeline for matrix-assisted laser
    desorption/ionization-time-of-flight (MALDI-TOF) and other two-dimensional mass
    spectrometry data. In addition to commonly used plotting and processing methods
    it includes distinctive features, namely baseline subtraction methods such as
    morphological filters (TopHat) or the statistics-sensitive non-linear iterative
    peak-clipping algorithm (SNIP), peak alignment using warping functions, handling
    of replicated measurements as well as allowing spectra with different resolutions.
  documentation:
  - note: null
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    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
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    note: null
    operation:
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    - term: Spectrum calculation
      uri: http://edamontology.org/operation_3860
    - term: Peak detection
      uri: http://edamontology.org/operation_3215
    output:
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        term: Report
        uri: http://edamontology.org/data_2048
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
  - cmd: null
    input:
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: imzML metadata file
        uri: http://edamontology.org/format_3682
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: ibd
        uri: http://edamontology.org/format_3839
    note: null
    operation:
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    output:
    - data:
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        uri: http://edamontology.org/data_2884
      format:
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        uri: http://edamontology.org/format_3603
  - cmd: null
    input:
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: imzML metadata file
        uri: http://edamontology.org/format_3682
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
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        uri: http://edamontology.org/format_3839
    note: null
    operation:
    - term: Mass spectra calibration
      uri: http://edamontology.org/operation_3627
    output:
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: imzML metadata file
        uri: http://edamontology.org/format_3682
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: ibd
        uri: http://edamontology.org/format_3839
  homepage: https://cran.r-project.org/package=MALDIquant
  homepage_status: 0
  language:
  - R
  lastUpdate: '2025-06-05T11:28:57.497366Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/sgibb/MALDIquant/
  - note: null
    type:
    - Issue tracker
    url: https://github.com/sgibb/MALDIquant/issues
  - note: null
    type:
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    url: http://strimmerlab.org/software/maldiquant/
  maturity: null
  name: MALDIquant
  operatingSystem: []
  otherID: []
  owner: Kigaard
  publication:
  - doi: 10.1093/bioinformatics/bts447
    metadata:
      abstract: MALDIquant is an R package providing a complete and modular analysis
        pipeline for quantitative analysis of mass spectrometry data. MALDIquant is
        specifically designed with application in clinical diagnostics in mind and
        implements sophisticated routines for importing raw data, preprocessing, non-linear
        peak alignment and calibration. It also handles technical replicates as well
        as spectra with unequal resolution. © The Author 2012. Published by Oxford
        University Press. All rights reserved.
      authors:
      - name: Gibb S.
      - name: Strimmer K.
      citationCount: 499
      date: '2012-09-01T00:00:00Z'
      journal: Bioinformatics
      title: 'Maldiquant: A versatile R package for the analysis of mass spectrometry
        data'
    note: null
    pmcid: null
    pmid: '22796955'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Library
  - Workflow
  topic:
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2017-02-10T14:14:47Z'
  biotoolsCURIE: biotools:act
  biotoolsID: act
  collectionID: []
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  cost: Free of charge
  credit:
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    fundrefid: null
    gridid: null
    name: David R Westhead
    note: null
    orcidid: https://orcid.org/0000-0002-0519-3820
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://biologicalsciences.leeds.ac.uk/molecular-and-cellular-biology/staff/154/professor-david-r-westhead
  - email: imichalop@bioacademy.gr
    fundrefid: null
    gridid: null
    name: Ioannis Michalopoulos
    note: null
    orcidid: https://orcid.org/0000-0001-8991-8712
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://www.michalopoulos.net/
  description: The Arabidopsis Coexpression Tool (ACT) is based on the coexpression
    analysis of 21273 Arabidopsis thaliana genes from gene pair correlation data of
    3500 Affymetrix Arabidopsis ATH1 Genome Array Chip microarray samples.
  documentation:
  - note: null
    type:
    - FAQ
    url: https://www.michalopoulos.net/act2.6/help.php
  download: []
  editPermission:
    authors:
    - imichalop@bioacademy.gr
    type: private
  elixirCommunity:
  - Plant Sciences
  elixirNode:
  - Greece
  elixirPlatform:
  - Tools
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Gene identifier
        uri: http://edamontology.org/data_1025
      format: []
    note: null
    operation:
    - term: Dendrogram visualisation
      uri: http://edamontology.org/operation_2938
    output:
    - data:
        term: Gene tree
        uri: http://edamontology.org/data_3271
      format: []
  homepage: https://www.michalopoulos.net/act/
  homepage_status: 0
  language: []
  lastUpdate: '2025-06-04T05:50:14.941224Z'
  license: null
  link: []
  maturity: Mature
  name: Arabidopsis Co-expression Tool (ACT)
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: imichalop@bioacademy.gr
  publication:
  - doi: 10.3390/genes16030258
    metadata:
      abstract: 'Background/Objectives: Genes with similar expression patterns across
        multiple samples are considered coexpressed, and they may participate in similar
        biological processes or pathways. Gene coexpression networks depict the degree
        of similarity between the expression profiles of all genes in a set of samples.
        Gene coexpression tools allow for the prediction of functional gene partners
        or the assignment of roles to genes of unknown function. Weighted Gene Correlation
        Network Analysis (WGCNA) is an R package that provides a multitude of functions
        for constructing and analyzing a weighted or unweighted gene coexpression
        network. Methods: Previously preprocessed, high-quality gene expression data
        of 3500 samples of Affymetrix microarray technology from various tissues of
        the Arabidopsis thaliana plant model species were used to construct a weighted
        gene coexpression network, using WGCNA. Results: The gene dendrogram was used
        as the basis for the creation of a new Arabidopsis coexpression tool (ACT)
        version (ACT2.6). The dendrogram contains 21,273 leaves, each one corresponding
        to a single gene. Genes that are clustered in the same clade are coexpressed.
        WGCNA grouped the genes into 27 functional modules, all of which were positively
        or negatively correlated with specific tissues. Discussion: Genes known to
        be involved in common metabolic pathways were discovered in the same module.
        By comparing the current ACT version with the previous one, it was shown that
        the new version outperforms the old one in discovering the functional connections
        between gene partners. ACT2.6 is a major upgrade over the previous version
        and a significant addition to the collection of public gene coexpression tools.'
      authors:
      - name: Zogopoulos V.L.
      - name: Papadopoulos K.
      - name: Malatras A.
      - name: Iconomidou V.A.
      - name: Michalopoulos I.
      citationCount: 0
      date: '2025-03-01T00:00:00Z'
      journal: Genes
      title: 'ACT2.6: Global Gene Coexpression Network in Arabidopsis thaliana Using
        WGCNA'
    note: null
    pmcid: PMC11942487
    pmid: '40149410'
    type:
    - Primary
    version: null
  - doi: 10.1016/j.xpro.2022.101208
    metadata:
      abstract: Coexpressed genes tend to participate in related biological processes.
        Gene coexpression analysis allows the discovery of functional gene partners
        or the assignment of biological roles to genes of unknown function. In this
        protocol, we describe the steps necessary to create a gene coexpression tree
        for Arabidopsis thaliana, using publicly available Affymetrix CEL microarray
        data. Because the computational analysis described here is highly dependent
        on sample quality, we detail an automatic quality control approach. For complete
        details on the use and execution of this protocol, please refer to Zogopoulos
        et al. (2021).
      authors:
      - name: Zogopoulos V.L.
      - name: Malatras A.
      - name: Michalopoulos I.
      citationCount: 6
      date: '2022-03-18T00:00:00Z'
      journal: STAR Protocols
      title: Gene coexpression analysis in Arabidopsis thaliana based on public microarray
        data
    note: null
    pmcid: PMC8885756
    pmid: '35243384'
    type:
    - Method
    version: null
  - doi: 10.3390/biology11071019
    metadata:
      abstract: Gene coexpression analysis constitutes a widely used practice for
        gene partner identification and gene function prediction, consisting of many
        intricate procedures. The analysis begins with the collection of primary transcriptomic
        data and their preprocessing, continues with the calculation of the similarity
        between genes based on their expression values in the selected sample dataset
        and results in the construction and visualisation of a gene coexpression network
        (GCN) and its evaluation using biological term enrichment analysis. As gene
        coexpression analysis has been studied ex-tensively, we present most parts
        of the methodology in a clear manner and the reasoning behind the selection
        of some of the techniques. In this review, we offer a comprehensive and comprehensi-ble
        account of the steps required for performing a complete gene coexpression
        analysis in eukary-otic organisms. We comment on the use of RNA‐Seq vs. microarrays,
        as well as the best practices for GCN construction. Furthermore, we recount
        the most popular webtools and standalone applications performing gene coexpression
        analysis, with details on their methods, features and outputs.
      authors:
      - name: Zogopoulos V.L.
      - name: Saxami G.
      - name: Malatras A.
      - name: Papadopoulos K.
      - name: Tsotra I.
      - name: Iconomidou V.A.
      - name: Michalopoulos I.
      citationCount: 11
      date: '2022-07-01T00:00:00Z'
      journal: Biology
      title: Approaches in Gene Coexpression Analysis in Eukaryotes
    note: null
    pmcid: PMC9312353
    pmid: '36101400'
    type:
    - Review
    version: null
  - doi: 10.1093/nar/gkl204
    metadata:
      abstract: The Arabidopsis Co-expression Tool, ACT, ranks the genes across a
        large microarray dataset according to how closely their expression follows
        the expression of a query gene. A database stores pre-calculated co-expression
        results for ∼21 800 genes based on data from over 300 arrays. These results
        can be corroborated by calculation of co-expression results for user-defined
        sub-sets of arrays or experiments from the NASC/GARNet array dataset. Clique
        Finder (CF) identifies groups of genes which are consistently co-expressed
        with each other across a user-defined co-expression list. The parameters can
        be altered easily to adjust cluster size and the output examined for optimal
        inclusion of genes with known biological roles. Alternatively, a Scatter Plot
        tool displays the correlation coefficients for all genes against two user-selected
        queries on a scatter plot which can be useful for visual identification of
        clusters of genes with similar r-values. User-input groups of genes can be
        highlighted on the scatter plots. Inclusion of genes with known biology in
        sets of genes identified using CF and Scatter Plot tools allows inferences
        to be made about the roles of the other genes in the set and both tools can
        therefore be used to generate short lists of genes for further characterization.
        ACT is freely available at www.Arabidopsis.leeds.ac.uk/ACT. © The Author 2006.
        Published by Oxford University Press. All rights reserved.
      authors:
      - name: Manfield I.W.
      - name: Jen C.-H.
      - name: Pinney J.W.
      - name: Michalopoulos I.
      - name: Bradford J.R.
      - name: Gilmartin P.M.
      - name: Westhead D.R.
      citationCount: 130
      date: '2006-07-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'Arabidopsis Co-expression Tool (ACT): Web server tools for microarray-based
        gene expression analysis'
    note: null
    pmcid: PMC1538833
    pmid: '16845059'
    type:
    - Other
    version: null
  - doi: 10.1111/j.1365-313x.2006.02681.x
    metadata:
      abstract: 'We present a new WWW-based tool for plant gene analysis, the Arabidopsis
        Co-Expression Tool (ACT), based on a large Arabidopsis thaliana microarray
        data set obtained from the Nottingham Arabidopsis Stock Centre. The co-expression
        analysis tool allows users to identify genes whose expression patterns are
        correlated across selected experiments or the complete data set. Results are
        accompanied by estimates of the statistical significance of the correlation
        relationships, expressed as probability (P) and expectation (E) values. Additionally,
        highly ranked genes on a correlation list can be examined using the novel
        CLIQUE FINDER tool to determine the sets of genes most likely to be regulated
        in a similar manner. In combination, these tools offer three levels of analysis:
        creation of correlation lists of co-expressed genes, refinement of these lists
        using two-dimensional scatter plots, and dissection into cliques of co-regulated
        genes. We illustrate the applications of the software by analysing genes encoding
        functionally related proteins, as well as pathways involved in plant responses
        to environmental stimuli. These analyses demonstrate novel biological relationships
        underlying the observed gene co-expression patterns. To demonstrate the ability
        of the software to develop testable hypotheses on gene function within a defined
        biological process we have used the example of cell wall biosynthesis genes.
        The resource is freely available at http://www.arabidopsis.leeds.ac.uk/ACT/.
        © 2006 The Authors.'
      authors:
      - name: Jen C.-H.
      - name: Manfield I.W.
      - name: Michalopoulos I.
      - name: Pinney J.W.
      - name: Willats W.G.T.
      - name: Gilmartin P.M.
      - name: Westhead D.R.
      citationCount: 65
      date: '2006-04-01T00:00:00Z'
      journal: Plant Journal
      title: 'The Arabidopsis co-expression tool (ACT): A WWW-based tool and database
        for microarray-based gene expression analysis'
    note: null
    pmcid: null
    pmid: '16623895'
    type:
    - Other
    version: null
  - doi: 10.1016/j.isci.2021.102848
    metadata:
      abstract: Gene coexpression analysis refers to the discovery of sets of genes
        which exhibit similar expression patterns across multiple transcriptomic data
        sets, such as microarray experiment data of public repositories. Arabidopsis
        Coexpression Tool (ACT), a gene coexpression analysis web tool for Arabidopsis
        thaliana, identifies genes which are correlated to a driver gene. Primary
        microarray data from ATH1 Affymetrix platform were processed with Single-Channel
        Array Normalization algorithm and combined to produce a coexpression tree
        which contains ∼21,000 A. thaliana genes. ACT was developed to present subclades
        of coexpressed genes, as well as to perform gene set enrichment analysis,
        being unique in revealing enriched transcription factors targeting coexpressed
        genes. ACT offers a simple and user-friendly interface producing working hypotheses
        which can be experimentally verified for the discovery of gene partnership,
        pathway membership, and transcriptional regulation. ACT analyses have been
        successful in identifying not only genes with coordinated ubiquitous expressions
        but also genes with tissue-specific expressions.
      authors:
      - name: Zogopoulos V.L.
      - name: Saxami G.
      - name: Malatras A.
      - name: Angelopoulou A.
      - name: Jen C.-H.
      - name: Duddy W.J.
      - name: Daras G.
      - name: Hatzopoulos P.
      - name: Westhead D.R.
      - name: Michalopoulos I.
      citationCount: 15
      date: '2021-08-20T00:00:00Z'
      journal: iScience
      title: 'Arabidopsis Coexpression Tool: a tool for gene coexpression analysis
        in Arabidopsis thaliana'
    note: null
    pmcid: PMC8334378
    pmid: '34381973'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Transcriptomics
    uri: http://edamontology.org/topic_3308
  validated: 1
  version:
  - '2.6'
- accessibility: Open access
  additionDate: '2025-06-03T11:42:31.433057Z'
  biotoolsCURIE: biotools:cnsistent
  biotoolsID: cnsistent
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: adam.streck@gmail.com
    fundrefid: null
    gridid: null
    name: Adam Streck
    note: null
    orcidid: https://orcid.org/0000-0002-7302-0147
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  description: Imputation, consistent segmentation, statistical analysis, and visualization
    of copy number profiles.
  documentation:
  - note: null
    type:
    - Command-line options
    - API documentation
    - Quick start guide
    url: https://cnsistent.readthedocs.io/
  download:
  - note: null
    type: Source code
    url: https://bitbucket.org/schwarzlab/cnsistent.git
    version: null
  - note: null
    type: Software package
    url: https://pypi.org/project/CNSistent/
    version: null
  editPermission:
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    type: private
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  function: []
  homepage: https://cnsistent.readthedocs.io
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-06-03T11:54:45.306699Z'
  license: MIT
  link: []
  maturity: Emerging
  name: CNSistent
  operatingSystem: []
  otherID: []
  owner: AdamStreck
  publication:
  - doi: 10.1101/2024.12.23.630118
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
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  description: SAMtools and BCFtools are widely used programs for processing and analysing
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    metadata:
      abstract: 'Summary: The Sequence Alignment/Map (SAM) format is a generic alignment
        format for storing read alignments against reference sequences, supporting
        short and long reads (up to 128 Mbp) produced by different sequencing platforms.
        It is flexible in style, compact in size, efficient in random access and is
        the format in which alignments from the 1000 Genomes Project are released.
        SAM tools implements various utilities for post-processing alignments in the
        SAM format, such as indexing, variant caller and alignment viewer, and thus
        provides universal tools for processing read alignments. © 2009 The Author(s).'
      authors:
      - name: Li H.
      - name: Handsaker B.
      - name: Wysoker A.
      - name: Fennell T.
      - name: Ruan J.
      - name: Homer N.
      - name: Marth G.
      - name: Abecasis G.
      - name: Durbin R.
      citationCount: 42239
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      journal: Bioinformatics
      title: The Sequence Alignment/Map format and SAMtools
    note: The Sequence Alignment/Map format and SAMtools.
    pmcid: PMC2723002
    pmid: '19505943'
    type:
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  - doi: 10.1093/gigascience/giab008
    metadata:
      abstract: 'Background: SAMtools and BCFtools are widely used programs for processing
        and analysing high-throughput sequencing data. They include tools for file
        format conversion and manipulation, sorting, querying, statistics, variant
        calling, and effect analysis amongst other methods. Findings: The first version
        appeared online 12 years ago and has been maintained and further developed
        ever since, with many new features and improvements added over the years.
        The SAMtools and BCFtools packages represent a unique collection of tools
        that have been used in numerous other software projects and countless genomic
        pipelines. Conclusion: Both SAMtools and BCFtools are freely available on
        GitHub under the permissive MIT licence, free for both non-commercial and
        commercial use. Both packages have been installed >1 million times via Bioconda.
        The source code and documentation are available from https://www.htslib.org.'
      authors:
      - name: Danecek P.
      - name: Bonfield J.K.
      - name: Liddle J.
      - name: Marshall J.
      - name: Ohan V.
      - name: Pollard M.O.
      - name: Whitwham A.
      - name: Keane T.
      - name: McCarthy S.A.
      - name: Davies R.M.
      citationCount: 6224
      date: '2021-02-01T00:00:00Z'
      journal: GigaScience
      title: Twelve years of SAMtools and BCFtools
    note: Twelve years of SAMtools and BCFtools.
    pmcid: PMC7931819
    pmid: '33590861'
    type:
    - Primary
    version: null
  - doi: 10.1093/bioinformatics/btr509
    metadata:
      abstract: 'Motivation: Most existing methods for DNA sequence analysis rely
        on accurate sequences or genotypes. However, in applications of the next-generation
        sequencing (NGS), accurate genotypes may not be easily obtained (e.g. multi-sample
        low-coverage sequencing or somatic mutation discovery). These applications
        press for the development of new methods for analyzing sequence data with
        uncertainty. Results: We present a statistical framework for calling SNPs,
        discovering somatic mutations, inferring population genetical parameters and
        performing association tests directly based on sequencing data without explicit
        genotyping or linkage-based imputation. On real data, we demonstrate that
        our method achieves comparable accuracy to alternative methods for estimating
        site allele count, for inferring allele frequency spectrum and for association
        mapping. We also highlight the necessity of using symmetric datasets for finding
        somatic mutations and confirm that for discovering rare events, mismapping
        is frequently the leading source of errors. © The Author 2011. Published by
        Oxford University Press. All rights reserved.'
      authors:
      - name: Li H.
      citationCount: 4405
      date: '2011-11-01T00:00:00Z'
      journal: Bioinformatics
      title: A statistical framework for SNP calling, mutation discovery, association
        mapping and population genetical parameter estimation from sequencing data
    note: null
    pmcid: PMC3198575
    pmid: '21903627'
    type: []
    version: null
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  - term: Sequence analysis
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  - term: Sequencing
    uri: http://edamontology.org/topic_3168
  - term: Rare diseases
    uri: http://edamontology.org/topic_3325
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  description: The main purpose of HTSlib is to provide access to genomic information
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    metadata:
      abstract: 'Background: Since the original publication of the VCF and SAM formats,
        an explosion of software tools have been created to process these data files.
        To facilitate this a library was produced out of the original SAMtools implementation,
        with a focus on performance and robustness. The file formats themselves have
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        been used directly by an estimated 900 GitHub projects and has been incorporated
        into Perl, Python, Rust, and R, significantly expanding the number of uses
        via other languages. HTSlib is open source and is freely available from htslib.org
        under MIT/BSD license.'
      authors:
      - name: Bonfield J.K.
      - name: Marshall J.
      - name: Danecek P.
      - name: Li H.
      - name: Ohan V.
      - name: Whitwham A.
      - name: Keane T.
      citationCount: 189
      date: '2021-02-01T00:00:00Z'
      journal: GigaScience
      title: 'HTSlib: C library for reading/writing high-Throughput sequencing data'
    note: 'HTSlib: C library for reading/writing high-throughput sequencing data.'
    pmcid: PMC7931820
    pmid: '33594436'
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    version: null
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  description: BCFtools is a set of utilities that manipulate variant calls in the
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    with both VCFs and BCFs, both uncompressed and BGZF-compressed.
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      - term: BCF
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    note: Multiple data munging operations.
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    output:
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      format:
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  maturity: Mature
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  otherID: []
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  publication:
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    metadata:
      abstract: 'Summary: The Sequence Alignment/Map (SAM) format is a generic alignment
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        short and long reads (up to 128 Mbp) produced by different sequencing platforms.
        It is flexible in style, compact in size, efficient in random access and is
        the format in which alignments from the 1000 Genomes Project are released.
        SAM tools implements various utilities for post-processing alignments in the
        SAM format, such as indexing, variant caller and alignment viewer, and thus
        provides universal tools for processing read alignments. © 2009 The Author(s).'
      authors:
      - name: Li H.
      - name: Handsaker B.
      - name: Wysoker A.
      - name: Fennell T.
      - name: Ruan J.
      - name: Homer N.
      - name: Marth G.
      - name: Abecasis G.
      - name: Durbin R.
      citationCount: 42239
      date: '2009-08-01T00:00:00Z'
      journal: Bioinformatics
      title: The Sequence Alignment/Map format and SAMtools
    note: The Sequence Alignment/Map format and SAMtools.
    pmcid: PMC2723002
    pmid: '19505943'
    type:
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    metadata:
      abstract: 'Background: SAMtools and BCFtools are widely used programs for processing
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        format conversion and manipulation, sorting, querying, statistics, variant
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        appeared online 12 years ago and has been maintained and further developed
        ever since, with many new features and improvements added over the years.
        The SAMtools and BCFtools packages represent a unique collection of tools
        that have been used in numerous other software projects and countless genomic
        pipelines. Conclusion: Both SAMtools and BCFtools are freely available on
        GitHub under the permissive MIT licence, free for both non-commercial and
        commercial use. Both packages have been installed >1 million times via Bioconda.
        The source code and documentation are available from https://www.htslib.org.'
      authors:
      - name: Danecek P.
      - name: Bonfield J.K.
      - name: Liddle J.
      - name: Marshall J.
      - name: Ohan V.
      - name: Pollard M.O.
      - name: Whitwham A.
      - name: Keane T.
      - name: McCarthy S.A.
      - name: Davies R.M.
      citationCount: 6224
      date: '2021-02-01T00:00:00Z'
      journal: GigaScience
      title: Twelve years of SAMtools and BCFtools
    note: Twelve years of SAMtools and BCFtools.
    pmcid: PMC7931819
    pmid: '33590861'
    type:
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    version: null
  relation:
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  topic:
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  - term: DNA polymorphism
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  - term: GWAS study
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  - term: Genotyping experiment
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  - '1.8'
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  - '1.15'
  - 1.15.1
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  - '1.20'
  - '1.21'
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- accessibility: Open access
  additionDate: '2025-05-31T07:43:57.081940Z'
  biotoolsCURIE: biotools:syngenes
  biotoolsID: syngenes
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  confidence_flag: tool
  cost: Free of charge
  credit:
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    fundrefid: null
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    name: Luan Pinto Rabelo
    note: null
    orcidid: null
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    typeEntity: Person
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  description: SynGenes is a Python class for standardizing Mitochondrial or Chloroplast
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    nomenclature variations into a standardized form.
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  maturity: null
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  operatingSystem:
  - Mac
  - Windows
  - Linux
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1186/s12859-024-05781-y
    metadata:
      abstract: 'Background: The reconstruction of the evolutionary history of organisms
        has been greatly influenced by the advent of molecular techniques, leading
        to a significant increase in studies utilizing genomic data from different
        species. However, the lack of standardization in gene nomenclature poses a
        challenge in database searches and evolutionary analyses, impacting the accuracy
        of results obtained. Results: To address this issue, a Python class for standardizing
        gene nomenclatures, SynGenes, has been developed. It automatically recognizes
        and converts different nomenclature variations into a standardized form, facilitating
        comprehensive and accurate searches. Additionally, SynGenes offers a web form
        for individual searches using different names associated with the same gene.
        The SynGenes database contains a total of 545 gene name variations for mitochondrial
        and 2485 for chloroplasts genes, providing a valuable resource for researchers.
        Conclusions: The SynGenes platform offers a solution for standardizing gene
        nomenclatures of mitochondrial and chloroplast genes and providing a standardized
        search solution for specific markers in GenBank. Evaluation of SynGenes effectiveness
        through research conducted on GenBank and PubMedCentral demonstrated its ability
        to yield a greater number of outcomes compared to conventional searches, ensuring
        more comprehensive and accurate results. This tool is crucial for accurate
        database searches, and consequently, evolutionary analyses, addressing the
        challenges posed by non-standardized gene nomenclature. Graphical abstract:
        (Figure presented.)'
      authors:
      - name: Rabelo L.P.
      - name: Sodre D.
      - name: de Sousa R.P.C.
      - name: Watanabe L.
      - name: Gomes G.
      - name: Sampaio I.
      - name: Vallinoto M.
      citationCount: 1
      date: '2024-12-01T00:00:00Z'
      journal: BMC Bioinformatics
      title: 'SynGenes: a Python class for standardizing nomenclatures of mitochondrial
        and chloroplast genes and a web form for enhancing searches for evolutionary
        analyses'
    note: null
    pmcid: PMC11036621
    pmid: '38649820'
    type: []
    version: null
  relation: []
  toolType: []
  topic:
  - term: Ontology and terminology
    uri: http://edamontology.org/topic_0089
  - term: Genetics
    uri: http://edamontology.org/topic_3053
  - term: Cell biology
    uri: http://edamontology.org/topic_2229
  - term: Biotechnology
    uri: http://edamontology.org/topic_3297
  - term: Phylogenetics
    uri: http://edamontology.org/topic_3293
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2025-05-30T11:22:28.697447Z'
  biotoolsCURIE: biotools:krakenparser
  biotoolsID: krakenparser
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: KrakenParser is a streamlined toolkit that transforms Kraken-2 taxonomic
    reports into tidy CSV files, automatically computes relative abundances, and exposes
    an intuitive API suite for effortless downstream visualization.
  documentation:
  - note: null
    type:
    - API documentation
    url: https://github.com/PopovIILab/KrakenParser/wiki
  - note: null
    type:
    - User manual
    url: https://github.com/PopovIILab/KrakenParser
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    note: null
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  - cmd: null
    input: []
    note: null
    operation:
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      uri: http://edamontology.org/operation_0337
    output: []
  homepage: https://github.com/PopovIILab/KrakenParser
  homepage_status: 0
  language:
  - Python
  - Shell
  lastUpdate: '2025-05-30T11:22:28.699989Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/PopovIILab/KrakenParser
  maturity: Emerging
  name: KrakenParser
  operatingSystem:
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  - Linux
  - Windows
  otherID: []
  owner: iliapopov17
  publication: []
  relation:
  - biotoolsID: krakentools
    type: uses
  toolType:
  - Command-line tool
  - Bioinformatics portal
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  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  - term: Taxonomy
    uri: http://edamontology.org/topic_0637
  validated: 0
  version:
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  - 0.1.62
  - 0.5.0
- accessibility: Open access
  additionDate: '2021-01-12T12:02:47Z'
  biotoolsCURIE: biotools:mugvre
  biotoolsID: mugvre
  collectionID:
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  confidence_flag: null
  cost: Free of charge
  credit:
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    fundrefid: null
    gridid: null
    name: Laia Codó
    note: null
    orcidid: https://orcid.org/0000-0002-6797-8746
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Josep Lluís Gelpí
    note: null
    orcidid: http://orcid.org/0000-0002-0566-7723
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  - email: vre@multiscalegenomics.eu
    fundrefid: null
    gridid: null
    name: Multiscale Complex Genomics Community
    note: null
    orcidid: null
    rorid: null
    typeEntity: Consortium
    typeRole:
    - Developer
    url: https://www.multiscalegenomics.eu/
  description: The MuG Virtual Research Environment is an analysis platform for 3D/4D
    genomics analyses. It integrates genomics tools for chromatin dynamics data.
  documentation:
  - note: null
    type:
    - Terms of use
    url: https://www.multiscalegenomics.eu/MuGVRE/terms-of-use/
  - note: null
    type:
    - Quick start guide
    url: http://vre.multiscalegenomics.eu/help/starting.php
  - note: null
    type:
    - Training material
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  download: []
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    type: group
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      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
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      format: []
    note: null
    operation:
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      uri: http://edamontology.org/operation_0292
    - term: Read mapping
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        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format:
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  - cmd: null
    input:
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      format:
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    - data:
        term: Sequence features
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      format:
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        uri: http://edamontology.org/format_2305
    note: null
    operation:
    - term: Nucleic acid structure prediction
      uri: http://edamontology.org/operation_0475
    - term: Modelling and simulation
      uri: http://edamontology.org/operation_2426
    - term: Nucleic acid folding analysis
      uri: http://edamontology.org/operation_0279
    output:
    - data:
        term: Trajectory data
        uri: http://edamontology.org/data_3870
      format: []
    - data:
        term: Protein structure
        uri: http://edamontology.org/data_1460
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
  - cmd: null
    input:
    - data:
        term: Protein structure
        uri: http://edamontology.org/data_1460
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
    note: null
    operation:
    - term: Molecular docking
      uri: http://edamontology.org/operation_0478
    - term: DNA-binding protein prediction
      uri: http://edamontology.org/operation_3900
    output:
    - data:
        term: Protein complex
        uri: http://edamontology.org/data_2877
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
  - cmd: null
    input:
    - data:
        term: Protein interaction raw data
        uri: http://edamontology.org/data_0905
      format:
      - term: BAM
        uri: http://edamontology.org/format_2572
    note: null
    operation:
    - term: Peak calling
      uri: http://edamontology.org/operation_3222
    - term: Gene regulatory network analysis
      uri: http://edamontology.org/operation_1781
    output:
    - data:
        term: Nucleic acid features
        uri: http://edamontology.org/data_1276
      format:
      - term: BED
        uri: http://edamontology.org/format_3003
  - cmd: null
    input:
    - data:
        term: Protein interaction raw data
        uri: http://edamontology.org/data_0905
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
    note: null
    operation:
    - term: Network analysis
      uri: http://edamontology.org/operation_3927
    - term: Nucleic acid folding analysis
      uri: http://edamontology.org/operation_0279
    output:
    - data:
        term: Topology data
        uri: http://edamontology.org/data_3872
      format:
      - term: pickle
        uri: http://edamontology.org/format_4002
    - data:
        term: Protein interaction data
        uri: http://edamontology.org/data_0906
      format:
      - term: pickle
        uri: http://edamontology.org/format_4002
  - cmd: null
    input:
    - data:
        term: Protein-ligand complex
        uri: http://edamontology.org/data_1461
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
    note: null
    operation:
    - term: Nucleic acid sequence analysis
      uri: http://edamontology.org/operation_2478
    output:
    - data:
        term: Nucleic acid report
        uri: http://edamontology.org/data_2084
      format: []
  - cmd: null
    input:
    - data:
        term: Structure
        uri: http://edamontology.org/data_0883
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
    note: null
    operation:
    - term: Molecular dynamics
      uri: http://edamontology.org/operation_2476
    - term: Nucleic acid structure analysis
      uri: http://edamontology.org/operation_2481
    output:
    - data:
        term: Trajectory data
        uri: http://edamontology.org/data_3870
      format: []
  - cmd: null
    input:
    - data:
        term: Protein interaction raw data
        uri: http://edamontology.org/data_0905
      format:
      - term: BAM
        uri: http://edamontology.org/format_2572
    note: null
    operation:
    - term: Nucleosome position prediction
      uri: http://edamontology.org/operation_0432
    - term: Phasing
      uri: http://edamontology.org/operation_3454
    output:
    - data:
        term: Annotation track
        uri: http://edamontology.org/data_3002
      format:
      - term: GFF
        uri: http://edamontology.org/format_2305
  - cmd: null
    input:
    - data:
        term: Sequence coordinates
        uri: http://edamontology.org/data_2012
      format: []
    - data:
        term: Annotation track
        uri: http://edamontology.org/data_3002
      format: []
    - data:
        term: Simulation
        uri: http://edamontology.org/data_3869
      format: []
    - data:
        term: Structure
        uri: http://edamontology.org/data_0883
      format: []
    note: null
    operation:
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    - term: Structure visualisation
      uri: http://edamontology.org/operation_0570
    - term: Sequence visualisation
      uri: http://edamontology.org/operation_0564
    - term: Network visualisation
      uri: http://edamontology.org/operation_3925
    output: []
  homepage: https://www.multiscalegenomics.eu/
  homepage_status: 0
  language:
  - PHP
  - Python
  lastUpdate: '2025-05-29T11:46:19.236621Z'
  license: Apache-2.0
  link:
  - note: null
    type:
    - Service
    url: http://vre.multiscalegenomics.eu
  - note: null
    type:
    - Repository
    url: https://github.com/Multiscale-Genomics/VRE
  maturity: null
  name: MuGVRE
  operatingSystem: []
  otherID: []
  owner: lcodo
  publication:
  - doi: 10.1101/602474
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: '1.0'
  relation:
  - biotoolsID: nucleosome_dynamics
    type: includes
  - biotoolsID: tadbit
    type: includes
  - biotoolsID: jbrowse
    type: includes
  - biotoolsID: ngl
    type: includes
  toolType:
  - Web application
  - Workbench
  topic:
  - term: DNA packaging
    uri: http://edamontology.org/topic_3176
  - term: ChIP-seq
    uri: http://edamontology.org/topic_3169
  - term: Nucleic acid structure analysis
    uri: http://edamontology.org/topic_0097
  - term: Molecular modelling
    uri: http://edamontology.org/topic_2275
  validated: 1
  version:
  - '1.0'
- accessibility: Open access
  additionDate: '2025-05-27T14:49:33.133482Z'
  biotoolsCURIE: biotools:nestedcombat
  biotoolsID: nestedcombat
  collectionID:
  - EUCAIM
  confidence_flag: tool
  cost: Free of charge
  credit: []
  description: 'This software performs feature-level harmonization of radiomic data
    extracted from medical images. Its primary goal is to reduce variability introduced
    by differences in acquisition protocols, scanner types, and imaging centers. The
    tool is based on the ComBat methodology, which uses an empirical Bayes linear
    model to correct batch effects by estimating location and scale parameters. It
    offers two harmonization strategies: the ComBat method, which aligns radiomic
    features to a common scale based on either all centers (ComBat) or a user-defined
    batch grouping (M-ComBat), and the Nested ComBat method, which enables simultaneous
    correction for multiple batch effects in hierarchical settings. This tool is intended
    to improve the robustness and comparability of radiomic features in multi-center
    studies.'
  documentation:
  - note: null
    type:
    - Quick start guide
    url: https://github.com/BenitoFar/NestedComBat
  download:
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    type: Source code
    url: https://github.com/BenitoFar/NestedComBat
    version: v1
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  homepage: https://github.com/BenitoFar/NestedComBat
  homepage_status: 0
  language:
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  lastUpdate: '2025-05-29T08:28:15.553602Z'
  license: MIT
  link: []
  maturity: Emerging
  name: NestedComBat
  operatingSystem:
  - Linux
  otherID: []
  owner: BenFar
  publication: []
  relation: []
  toolType:
  - Command-line tool
  topic:
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    uri: http://edamontology.org/topic_3474
  - term: Statistics and probability
    uri: http://edamontology.org/topic_2269
  validated: 0
  version:
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- accessibility: Open access
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  biotoolsCURIE: biotools:human_microbiome_compendium
  biotoolsID: human_microbiome_compendium
  collectionID:
  - microbiome
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: rabdill@uchicago.edu
    fundrefid: null
    gridid: null
    name: Richard Abdill
    note: null
    orcidid: https://orcid.org/0000-0001-9565-5832
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://blekhmanlab.org
  description: Collection of human microbiome sequencing data that pairs subject metadata
    with relative abundance data derived from amplicon and shotgun metagenomic sequencing
    processed via uniform pipelines.
  documentation:
  - note: null
    type:
    - User manual
    url: https://zenodo.org/records/15122187/files/README.md
  download:
  - note: DOI links to the most recent release
    type: Biological data
    url: https://doi.org/10.5281/zenodo.8186993
    version: null
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  homepage: https://microbiomap.org
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  language:
  - R
  - Python
  lastUpdate: '2025-05-27T01:09:26.566817Z'
  license: CC-BY-2.0
  link:
  - note: Homepage of the project with links to multiple tools and datasets
    type:
    - Other
    url: https://microbiomap.org
  - note: Link to the most recent release of the compendium dataset
    type:
    - Repository
    url: https://doi.org/10.5281/zenodo.8186993
  maturity: Emerging
  name: Human Microbiome Compendium
  operatingSystem: []
  otherID:
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    value: RRID:SCR_026991
    version: null
  owner: rabdill
  publication:
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    metadata: null
    note: null
    pmcid: PMC11848717
    pmid: '39848248'
    type:
    - Primary
    version: 1.1.0
  relation: []
  toolType:
  - Bioinformatics portal
  topic:
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  - term: Microbial ecology
    uri: http://edamontology.org/topic_3697
  - term: FAIR data
    uri: http://edamontology.org/topic_4012
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  - term: Phylogenetics
    uri: http://edamontology.org/topic_3293
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2023-07-13T08:14:40.190855Z'
  biotoolsCURIE: biotools:nlmced_filter
  biotoolsID: nlmced_filter
  collectionID:
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  confidence_flag: null
  cost: null
  credit: []
  description: The NLmCED (Non Local mean Coherence Enhancing Diffusion) filter is
    a denoising tool aimed to reduce Rician Noise in 3D MR images. It is a combination
    between two filters such as the Non-Local mean filter and the Anisotropic Diffusion
    tensor method with an estimator of Rician noise. The NLmCED filter can benefit
    from the noise reduction capabilities of the NLM filter while maintaining the
    edge-preserving characteristics of anisotropic diffusion.
  documentation: []
  download: []
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  elixir_badge: 0
  function:
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    input:
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        term: Image
        uri: http://edamontology.org/data_2968
      format:
      - term: DICOM format
        uri: http://edamontology.org/format_3548
    note: null
    operation:
    - term: Image analysis
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    - term: Data filtering
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    output:
    - data:
        term: Image
        uri: http://edamontology.org/data_2968
      format:
      - term: DICOM format
        uri: http://edamontology.org/format_3548
  homepage: https://github.com/Feriel87/Denoising-CEST-MRI/tree/main/NLmCED_Filter
  homepage_status: 0
  language:
  - MATLAB
  lastUpdate: '2025-05-22T12:21:15.198535Z'
  license: null
  link:
  - note: Github Link
    type:
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  name: NLmCED Filter
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  owner: Feriel
  publication:
  - doi: 10.1504/IJCVR.2018.090012
    metadata:
      abstract: Removing noise in magnetic resonance images (MRI) is a crucial issue
        in the field of medical image processing. These images are infected by Rician
        noise which is a non-Additive noise, allows to reduce the image contrast and
        causes random fluctuations. Our paper proposed a new method for 3D MRI denoising
        based on new combination between non-local means filter and the diffusion
        tensor with adaptative MAD estimator Rician noise. The performance of our
        proposed algorithm was evaluated with respect to different quantitative measures,
        compared to other denoising methods which illustrate that our proposed denoising
        algorithm efficiently removes noise and preserves more details.
      authors:
      - name: Romdhane F.
      - name: Benzarti F.
      - name: Amiri H.
      citationCount: 3
      date: '2018-01-01T00:00:00Z'
      journal: International Journal of Computational Vision and Robotics
      title: A new method for three-dimensional magnetic resonance images denoising
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType:
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  topic:
  - term: Imaging
    uri: http://edamontology.org/topic_3382
  - term: MRI
    uri: http://edamontology.org/topic_3444
  - term: Medical imaging
    uri: http://edamontology.org/topic_3384
  validated: 0
  version: []
next: ?page=2
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