count: 29595
list:
- accessibility: null
  additionDate: '2023-06-21T16:32:23.746446Z'
  biotoolsCURIE: biotools:massivefold
  biotoolsID: massivefold
  collectionID: []
  community: null
  confidence_flag: null
  cost: null
  credit: []
  description: MassiveFold allows massive sampling with AlphaFold or ColabFold, splitting
    the computing on CPUs and many GPUs.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Protein structure prediction
      uri: http://edamontology.org/operation_0474
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Multiple sequence alignment
      uri: http://edamontology.org/operation_0492
    output: []
  homepage: https://github.com/GBLille/MassiveFold
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2024-04-22T13:17:03.098045Z'
  license: null
  link: []
  maturity: null
  name: MassiveFold
  operatingSystem:
  - Linux
  - Mac
  - Windows
  otherID: []
  owner: gbrysbaert
  publication: []
  relation: []
  toolType: []
  topic:
  - term: Structure prediction
    uri: http://edamontology.org/topic_0082
  validated: 0
  version:
  - '1.2'
- accessibility: null
  additionDate: '2017-07-20T18:20:28Z'
  biotoolsCURIE: biotools:bridgedb_api
  biotoolsID: bridgedb_api
  collectionID:
  - Rare Disease
  - BridgeDb
  community: null
  confidence_flag: null
  cost: null
  credit:
  - email: bridgedb-discuss@googlegroups.com
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: 'BridgeDb is a framework for finding and mapping equivalent database
    identifiers. It has many facets: it is both a framework, live services, and are
    identifier mapping files for genes, proteins, and metabolites.'
  documentation:
  - note: null
    type:
    - General
    url: https://www.bridgedb.org/
  download: []
  editPermission:
    authors:
    - ChrisEvelo
    - LanfearJ
    type: group
  elixirCommunity: []
  elixirNode:
  - Netherlands
  elixirPlatform:
  - Interoperability
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Data
        uri: http://edamontology.org/data_0006
      format: []
    - data:
        term: Identifier
        uri: http://edamontology.org/data_0842
      format: []
    - data:
        term: Identifier
        uri: http://edamontology.org/data_0842
      format: []
    note: Returns a list of xrefs that map to a given identifier, and data source.
      Optionally restrict results to a given data source.
    operation:
    - term: Data retrieval
      uri: http://edamontology.org/operation_2422
    output:
    - data:
        term: Data
        uri: http://edamontology.org/data_0006
      format: []
  - cmd: null
    input:
    - data:
        term: Species name
        uri: http://edamontology.org/data_1045
      format: []
    - data:
        term: Identifier
        uri: http://edamontology.org/data_0842
      format: []
    - data:
        term: Identifier
        uri: http://edamontology.org/data_0842
      format: []
    note: Returns `true` or `false` based on whether or not an xref exists in the
      database given an identifier, data source, and organism.
    operation:
    - term: Data retrieval
      uri: http://edamontology.org/operation_2422
    output:
    - data:
        term: Data
        uri: http://edamontology.org/data_0006
      format: []
  homepage: http://www.bridgedb.org/
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2024-04-22T13:11:17.887951Z'
  license: null
  link: []
  maturity: null
  name: BridgeDb API
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: egonw
  publication:
  - doi: null
    metadata:
      abstract: 'Background: Many complementary solutions are available for the identifier
        mapping problem. This creates an opportunity for bioinformatics tool developers.
        Tools can be made to flexibly support multiple mapping services or mapping
        services could be combined to get broader coverage. This approach requires
        an interface layer between tools and mapping services.Results: Here we present
        BridgeDb, a software framework for gene, protein and metabolite identifier
        mapping. This framework provides a standardized interface layer through which
        bioinformatics tools can be connected to different identifier mapping services.
        This approach makes it easier for tool developers to support identifier mapping.
        Mapping services can be combined or merged to support multi-omics experiments
        or to integrate custom microarray annotations. BridgeDb provides its own ready-to-go
        mapping services, both in webservice and local database forms. However, the
        framework is intended for customization and adaptation to any identifier mapping
        service. BridgeDb has already been integrated into several bioinformatics
        applications.Conclusion: By uncoupling bioinformatics tools from mapping services,
        BridgeDb improves capability and flexibility of those tools. All described
        software is open source and available at http://www.bridgedb.org. © 2010 van
        Iersel et al; licensee BioMed Central Ltd.'
      authors:
      - name: van Iersel M.P.
      - name: Pico A.R.
      - name: Kelder T.
      - name: Gao J.
      - name: Ho I.
      - name: Hanspers K.
      - name: Conklin B.R.
      - name: Evelo C.T.
      citationCount: 123
      date: '2010-01-04T00:00:00Z'
      journal: BMC Bioinformatics
      title: 'The BridgeDb framework: Standardized access to gene, protein and metabolite
        identifier mapping services'
    note: null
    pmcid: null
    pmid: '20047655'
    type: []
    version: null
  relation: []
  toolType:
  - Web API
  topic:
  - term: Data identity and mapping
    uri: http://edamontology.org/topic_3345
  - term: Rare diseases
    uri: http://edamontology.org/topic_3325
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2024-04-19T11:31:13.116284Z'
  biotoolsCURIE: biotools:lion_localizer
  biotoolsID: lion_localizer
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: roca@illinois.edu
    fundrefid: null
    gridid: null
    name: Alfred L Roca
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Wesley C Au
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: Software tool for inferring the provenance of lions (Panthera leo)
    using mitochondrial DNA.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Sequence trimming
      uri: http://edamontology.org/operation_3192
    - term: Query and retrieval
      uri: http://edamontology.org/operation_0224
    - term: Haplotype mapping
      uri: http://edamontology.org/operation_0487
    output: []
  homepage: https://lionlocalizer.org
  homepage_status: 0
  language: []
  lastUpdate: '2024-04-19T11:31:13.118404Z'
  license: null
  link: []
  maturity: null
  name: Lion Localizer
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1093/JHERED/ESAD072
    metadata:
      abstract: The illegal poaching of lions for their body parts poses a severe
        threat to lion populations across Africa. Poaching accounts for 35% of all
        human-caused lion deaths, with 51% attributed to retaliatory killings following
        livestock predation. In nearly half of the retaliatory killings, lion body
        parts are removed, suggesting that high demand for lion body parts may fuel
        killings attributed to human-lion conflict. Trafficked items are often confiscated
        in transit or destination countries far from their country of origin. DNA
        from lion parts may in some cases be the only available means for examining
        their geographic origins. In this paper, we present the Lion Localizer, a
        full-stack software tool that houses a comprehensive database of lion mitochondrial
        DNA (mtDNA) sequences sourced from previously published studies. The database
        covers 146 localities from across the African continent and India, providing
        information on the potential provenance of seized lion body parts. Lion mtDNA
        sequences of 350 or 1,140 bp corresponding to the cytochrome b region can
        be generated from lion products and queried against the Lion Localizer database.
        Using the query sequence, the Lion Localizer generates a listing of exact
        or partial matches, which are displayed on an interactive map of Africa. This
        allows for the rapid identification of potential regions and localities where
        lions have been or are presently being targeted by poachers. By examining
        the potential provenance of lion samples, the Lion Localizer serves as a valuable
        resource in the fight against lion poaching. The software is available at
        https://lionlocalizer.org.
      authors:
      - name: Au W.C.
      - name: Dures S.G.
      - name: Ishida Y.
      - name: Green C.E.
      - name: Zhao K.
      - name: Ogden R.
      - name: Roca A.L.
      citationCount: 0
      date: '2024-03-01T00:00:00Z'
      journal: Journal of Heredity
      title: 'Lion Localizer: A software tool for inferring the provenance of lions
        (Panthera leo) using mitochondrial DNA'
    note: null
    pmcid: null
    pmid: '37952226'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Sequencing
    uri: http://edamontology.org/topic_3168
  - term: DNA
    uri: http://edamontology.org/topic_0654
  - term: Mapping
    uri: http://edamontology.org/topic_0102
  - term: Model organisms
    uri: http://edamontology.org/topic_0621
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2024-04-19T11:28:09.722051Z'
  biotoolsCURIE: biotools:metgene
  biotoolsID: metgene
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: shsubramaniam@ucsd.edu
    fundrefid: null
    gridid: null
    name: Shankar Subramaniam
    note: null
    orcidid: https://orcid.org/0000-0002-8059-4659
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Sumana Srinivasan
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: Gene-centric metabolomics information retrieval tool.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Data retrieval
      uri: http://edamontology.org/operation_2422
    - term: Aggregation
      uri: http://edamontology.org/operation_3436
    - term: Filtering
      uri: http://edamontology.org/operation_3695
    - term: Natural product identification
      uri: http://edamontology.org/operation_3803
    output: []
  homepage: https://bdcw.org/MetGENE/index.php
  homepage_status: 0
  language:
  - PHP
  - R
  lastUpdate: '2024-04-19T11:28:09.723894Z'
  license: null
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/metabolomicsworkbench/MetGENE
  maturity: null
  name: MetGENE
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1093/GIGASCIENCE/GIAD089
    metadata:
      abstract: 'Background: Biomedical research often involves contextual integration
        of multimodal and multiomic data in search of mechanisms for improved diagnosis,
        treatment, and monitoring. Researchers need to access information from diverse
        sources, comprising data in various and sometimes incongruent formats. The
        downstream processing of the data to decipher mechanisms by reconstructing
        networks and developing quantitative models warrants considerable effort.
        Results: MetGENE is a knowledge-based, gene-centric data aggregator that hierarchically
        retrieves information about the gene(s), their related pathway(s), reaction(s),
        metabolite(s), and metabolomic studies from standard data repositories under
        one dashboard to enable ease of access through centralization of relevant
        information. We note that MetGENE focuses only on those genes that encode
        for proteins directly associated with metabolites. All other gene–metabolite
        associations are beyond the current scope of MetGENE. Further, the information
        can be contextualized by filtering by species, anatomy (tissue), and condition
        (disease or phenotype). Conclusions: MetGENE is an open-source tool that aggregates
        metabolite information for a given gene(s) and presents them in different
        computable formats (e.g., JSON) for further integration with other omics studies.
        MetGENE is available at https://bdcw.org/MetGENE/index.php.'
      authors:
      - name: Srinivasan S.
      - name: Maurya M.R.
      - name: Ramachandran S.
      - name: Fahy E.
      - name: Subramaniam S.
      citationCount: 0
      date: '2023-01-01T00:00:00Z'
      journal: GigaScience
      title: 'MetGENE: gene-centric metabolomics information retrieval tool'
    note: null
    pmcid: PMC10659118
    pmid: '37983749'
    type: []
    version: null
  relation: []
  toolType:
  - Database portal
  topic:
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  - term: Genotype and phenotype
    uri: http://edamontology.org/topic_0625
  - term: Anatomy
    uri: http://edamontology.org/topic_3067
  validated: 0
  version: []
- accessibility: null
  additionDate: '2024-04-19T10:42:15.957876Z'
  biotoolsCURIE: biotools:pecat
  biotoolsID: pecat
  collectionID: []
  community: null
  confidence_flag: high
  cost: null
  credit:
  - email: xiaochuanle@126.com
    fundrefid: null
    gridid: null
    name: Chuanle Xiao
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: luofeng@clemson.edu
    fundrefid: null
    gridid: null
    name: Feng Luo
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: jxwang@mail.csu.edu.cn
    fundrefid: null
    gridid: null
    name: Jianxin Wang
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: De novo diploid genome assembly using long noisy reads.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Genome assembly
      uri: http://edamontology.org/operation_0525
    - term: De-novo assembly
      uri: http://edamontology.org/operation_0524
    - term: Phasing
      uri: http://edamontology.org/operation_3454
    - term: k-mer counting
      uri: http://edamontology.org/operation_3472
    - term: Haplotype mapping
      uri: http://edamontology.org/operation_0487
    output: []
  homepage: https://github.com/lemene/PECAT
  homepage_status: 0
  language: []
  lastUpdate: '2024-04-19T10:42:15.960256Z'
  license: null
  link: []
  maturity: null
  name: PECAT
  operatingSystem: []
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1038/s41467-024-47349-7
    metadata:
      abstract: The high sequencing error rate has impeded the application of long
        noisy reads for diploid genome assembly. Most existing assemblers failed to
        generate high-quality phased assemblies using long noisy reads. Here, we present
        PECAT, a Phased Error Correction and Assembly Tool, for reconstructing diploid
        genomes from long noisy reads. We design a haplotype-aware error correction
        method that can retain heterozygote alleles while correcting sequencing errors.
        We combine a corrected read SNP caller and a raw read SNP caller to further
        improve the identification of inconsistent overlaps in the string graph. We
        use a grouping method to assign reads to different haplotype groups. PECAT
        efficiently assembles diploid genomes using Nanopore R9, PacBio CLR or Nanopore
        R10 reads only. PECAT generates more contiguous haplotype-specific contigs
        compared to other assemblers. Especially, PECAT achieves nearly haplotype-resolved
        assembly on B. taurus (Bison×Simmental) using Nanopore R9 reads and phase
        block NG50 with 59.4/58.0 Mb for HG002 using Nanopore R10 reads.
      authors:
      - name: Nie F.
      - name: Ni P.
      - name: Huang N.
      - name: Zhang J.
      - name: Wang Z.
      - name: Xiao C.
      - name: Luo F.
      - name: Wang J.
      citationCount: 0
      date: '2024-12-01T00:00:00Z'
      journal: Nature Communications
      title: De novo diploid genome assembly using long noisy reads
    note: null
    pmcid: PMC10997618
    pmid: '38580638'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  - term: DNA polymorphism
    uri: http://edamontology.org/topic_2885
  - term: Mapping
    uri: http://edamontology.org/topic_0102
  validated: 0
  version: []
- accessibility: null
  additionDate: '2024-04-19T10:41:09.190574Z'
  biotoolsCURIE: biotools:vibes
  biotoolsID: vibes
  collectionID: []
  community: null
  confidence_flag: high
  cost: Free of charge
  credit:
  - email: twheeler@arizona.edu
    fundrefid: null
    gridid: null
    name: Travis J. Wheeler
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: Workflow for annotating and visualizing viral sequences integrated
    into bacterial genomes.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Genome annotation
      uri: http://edamontology.org/operation_0362
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    - term: Database search
      uri: http://edamontology.org/operation_2421
    output: []
  homepage: https://github.com/TravisWheelerLab/VIBES
  homepage_status: 0
  language:
  - Python
  - Perl
  lastUpdate: '2024-04-19T10:41:09.193087Z'
  license: BSD-3-Clause
  link: []
  maturity: null
  name: VIBES
  operatingSystem: []
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1093/nargab/lqae030
    metadata:
      abstract: Bacteriophages are viruses that infect bacteria. Many bacteriophages
        integrate their genomes into the bacterial chromosome and become prophages.
        Prophages may substantially burden or benefit host bacteria fitness, acting
        in some cases as parasites and in others as mutualists. Some prophages have
        been demonstrated to increase host virulence. The increasing ease of bacterial
        genome sequencing provides an opportunity to deeply explore prophage prevalence
        and insertion sites. Here we present VIBES (Viral Integrations in Bacterial
        genomES), a workflow intended to automate prophage annotation in complete
        bacterial genome sequences. VIBES provides additional context to prophage
        annotations by annotating bacterial genes and viral proteins in user-provided
        bacterial and viral genomes. The VIBES pipeline is implemented as a Nextflow-driven
        workflow, providing a simple, unified interface for execution on local, cluster
        and cloud computing environments. For each step of the pipeline, a container
        including all necessary software dependencies is provided. VIBES produces
        results in simple tab-separated format and generates intuitive and interactive
        visualizations for data exploration. Despite VIBES's primary emphasis on prophage
        annotation, its generic alignment-based design allows it to be deployed as
        a general-purpose sequence similarity search manager. We demonstrate the utility
        of the VIBES prophage annotation workflow by searching for 178 Pf phage genomes
        across 1072 Pseudomonas spp. genomes.
      authors:
      - name: Copeland C.J.
      - name: Roddy J.W.
      - name: Schmidt A.K.
      - name: Secor P.R.
      - name: Wheeler T.J.
      citationCount: 0
      date: '2024-06-01T00:00:00Z'
      journal: NAR Genomics and Bioinformatics
      title: 'VIBES: a workflow for annotating and visualizing viral sequences integrated
        into bacterial genomes'
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType:
  - Workflow
  topic:
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  - term: Workflows
    uri: http://edamontology.org/topic_0769
  - term: Whole genome sequencing
    uri: http://edamontology.org/topic_3673
  - term: Computer science
    uri: http://edamontology.org/topic_3316
  - term: Sequence sites, features and motifs
    uri: http://edamontology.org/topic_0160
  validated: 0
  version: []
- accessibility: null
  additionDate: '2024-04-19T10:38:47.438759Z'
  biotoolsCURIE: biotools:hista
  biotoolsID: hista
  collectionID: []
  community: null
  confidence_flag: high
  cost: null
  credit:
  - email: conradon@ohsu.edu
    fundrefid: null
    gridid: null
    name: Donald F. Conrad
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: An interactive molecular scRNA-Seq reference of the human testis.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Expression correlation analysis
      uri: http://edamontology.org/operation_3463
    - term: Gene expression profiling
      uri: http://edamontology.org/operation_0314
    - term: Database search
      uri: http://edamontology.org/operation_2421
    output: []
  homepage: https://conradlab.shinyapps.io/HISTA
  homepage_status: 0
  language:
  - R
  lastUpdate: '2024-04-19T10:38:47.441154Z'
  license: null
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/eisascience/HISTA
  - note: null
    type:
    - Other
    url: https://humantestisatlas.shinyapps.io/humantestisatlas1/
  maturity: null
  name: HISTA
  operatingSystem: []
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1111/andr.13637
    metadata: null
    note: null
    pmcid: null
    pmid: '38577799'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Functional, regulatory and non-coding RNA
    uri: http://edamontology.org/topic_0659
  - term: Gene expression
    uri: http://edamontology.org/topic_0203
  - term: Pathology
    uri: http://edamontology.org/topic_0634
  - term: Genotype and phenotype
    uri: http://edamontology.org/topic_0625
  - term: Gene transcripts
    uri: http://edamontology.org/topic_3512
  validated: 0
  version: []
- accessibility: null
  additionDate: '2024-04-19T10:32:44.536054Z'
  biotoolsCURIE: biotools:drava
  biotoolsID: drava
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Qianwen Wang
    note: null
    orcidid: https://orcid.org/0000-0003-1728-4102
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  description: Aligning human concepts with machine learning latent dimensions for
    the visual exploration of small multiples.
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    operation:
    - term: Visualisation
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    - term: Dimensionality reduction
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    - term: Essential dynamics
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  homepage: https://qianwen.info/DRAVA/
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  name: Drava
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  publication:
  - doi: 10.1145/3544548.3581127
    metadata:
      abstract: Latent vectors extracted by machine learning (ML) are widely used
        in data exploration (e.g., t-SNE) but suffer from a lack of interpretability.
        While previous studies employed disentangled representation learning (DRL)
        to enable more interpretable exploration, they often overlooked the potential
        mismatches between the concepts of humans and the semantic dimensions learned
        by DRL. To address this issue, we propose Drava, a visual analytics system
        that supports users in 1) relating the concepts of humans with the semantic
        dimensions of DRL and identifying mismatches, 2) providing feedback to minimize
        the mismatches, and 3) obtaining data insights from concept-driven exploration.
        Drava provides a set of visualizations and interactions based on visual piles
        to help users understand and refine concepts and conduct concept-driven exploration.
        Meanwhile, Drava employs a concept adaptor model to fine-tune the semantic
        dimensions of DRL based on user refinement. The usefulness of Drava is demonstrated
        through application scenarios and experimental validation.
      authors:
      - name: Wang Q.
      - name: L'Yi S.
      - name: Gehlenborg N.
      citationCount: 2
      date: '2023-04-19T00:00:00Z'
      journal: Conference on Human Factors in Computing Systems - Proceedings
      title: 'DRAVA: Aligning Human Concepts with Machine Learning Latent Dimensions
        for the Visual Exploration of Small Multiples'
    note: null
    pmcid: PMC10707479
    pmid: '38074525'
    type: []
    version: null
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  toolType:
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  topic:
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    uri: http://edamontology.org/topic_3474
  - term: Physics
    uri: http://edamontology.org/topic_3318
  - term: Imaging
    uri: http://edamontology.org/topic_3382
  validated: 0
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- accessibility: null
  additionDate: '2024-04-19T10:29:44.116723Z'
  biotoolsCURIE: biotools:chemprop
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  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: mcgillc2@vcu.edu
    fundrefid: null
    gridid: null
    name: Charles J. McGill
    note: null
    orcidid: https://orcid.org/0000-0003-2704-7717
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    url: null
  description: Machine learning package for chemical property prediction.
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    operation:
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    - term: Quantification
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    - term: Scaffolding
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    - term: Splitting
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    output: []
  homepage: http://github.com/chemprop/chemprop
  homepage_status: 0
  language:
  - Python
  - Shell
  - D
  lastUpdate: '2024-04-19T10:29:44.118952Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: http://github.com/chemprop/chemprop_benchmark
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  name: Chemprop
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  owner: Pub2Tools
  publication:
  - doi: 10.1021/ACS.JCIM.3C01250
    metadata:
      abstract: Deep learning has become a powerful and frequently employed tool for
        the prediction of molecular properties, thus creating a need for open-source
        and versatile software solutions that can be operated by nonexperts. Among
        the current approaches, directed message-passing neural networks (D-MPNNs)
        have proven to perform well on a variety of property prediction tasks. The
        software package Chemprop implements the D-MPNN architecture and offers simple,
        easy, and fast access to machine-learned molecular properties. Compared to
        its initial version, we present a multitude of new Chemprop functionalities
        such as the support of multimolecule properties, reactions, atom/bond-level
        properties, and spectra. Further, we incorporate various uncertainty quantification
        and calibration methods along with related metrics as well as pretraining
        and transfer learning workflows, improved hyperparameter optimization, and
        other customization options concerning loss functions or atom/bond features.
        We benchmark D-MPNN models trained using Chemprop with the new reaction, atom-level,
        and spectra functionality on a variety of property prediction data sets, including
        MoleculeNet and SAMPL, and observe state-of-the-art performance on the prediction
        of water-octanol partition coefficients, reaction barrier heights, atomic
        partial charges, and absorption spectra. Chemprop enables out-of-the-box training
        of D-MPNN models for a variety of problem settings in fast, user-friendly,
        and open-source software.
      authors:
      - name: Heid E.
      - name: Greenman K.P.
      - name: Chung Y.
      - name: Li S.-C.
      - name: Graff D.E.
      - name: Vermeire F.H.
      - name: Wu H.
      - name: Green W.H.
      - name: McGill C.J.
      citationCount: 7
      date: '2024-01-08T00:00:00Z'
      journal: Journal of Chemical Information and Modeling
      title: 'Chemprop: A Machine Learning Package for Chemical Property Prediction'
    note: null
    pmcid: PMC10777403
    pmid: '38147829'
    type: []
    version: null
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  toolType:
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  topic:
  - term: Machine learning
    uri: http://edamontology.org/topic_3474
  - term: NMR
    uri: http://edamontology.org/topic_0593
  - term: Chemistry
    uri: http://edamontology.org/topic_3314
  - term: Endocrinology and metabolism
    uri: http://edamontology.org/topic_3407
  - term: Molecular biology
    uri: http://edamontology.org/topic_3047
  validated: 0
  version: []
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  additionDate: '2024-04-19T10:26:21.921850Z'
  biotoolsCURIE: biotools:mcptaggr
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  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: f.tomoyuki@okayama-u.ac.jp
    fundrefid: null
    gridid: null
    name: Tomoyuki Furuta
    note: null
    orcidid: https://orcid.org/0000-0002-0869-6626
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: R package for accurate genotype calling in reduced representation sequencing
    data by eliminating error-prone markers based on genome comparison.
  documentation:
  - note: null
    type:
    - User manual
    url: https://tomoyukif.github.io/MCPtaggR/
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  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Genotyping
      uri: http://edamontology.org/operation_3196
    - term: Demultiplexing
      uri: http://edamontology.org/operation_3933
    - term: SNP detection
      uri: http://edamontology.org/operation_0484
    - term: De-novo assembly
      uri: http://edamontology.org/operation_0524
    output: []
  homepage: https://github.com/tomoyukif/MCPtaggR
  homepage_status: 0
  language:
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  lastUpdate: '2024-04-19T10:26:21.924007Z'
  license: GPL-3.0
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  publication:
  - doi: 10.1093/DNARES/DSAD027
    metadata:
      abstract: Reduced representation sequencing (RRS) offers cost-effective, high-throughput
        genotyping platforms such as genotyping-by-sequencing (GBS). RRS reads are
        typically mapped onto a reference genome. However, mapping reads harbouring
        mismatches against the reference can potentially result in mismapping and
        biased mapping, leading to the detection of error-prone markers that provide
        incorrect genotype information. We established a genotype-calling pipeline
        named mappable collinear polymorphic tag genotyping (MCPtagg) to achieve accurate
        genotyping by eliminating error-prone markers. MCPtagg was designed for the
        RRS-based genotyping of a population derived from a biparental cross. The
        MCPtagg pipeline filters out error-prone markers prior to genotype calling
        based on marker collinearity information obtained by comparing the genome
        sequences of the parents of a population to be genotyped. A performance evaluation
        on real GBS data from a rice F2 population confirmed its effectiveness. Furthermore,
        our performance test using a genome assembly that was obtained by genome sequence
        polishing on an available genome assembly suggests that our pipeline performs
        well with converted genomes, rather than necessitating de novo assembly. This
        demonstrates its flexibility and scalability. The R package, MCPtaggR, was
        developed to provide functions for the pipeline and is available at https://github.com/tomoyukif/MCPtaggR.
      authors:
      - name: Furuta T.
      - name: Yamamoto T.
      citationCount: 0
      date: '2024-02-01T00:00:00Z'
      journal: DNA Research
      title: 'MCPtaggR: R package for accurate genotype calling in reduced representation
        sequencing data by eliminating error-prone markers based on genome comparison'
    note: null
    pmcid: PMC10799318
    pmid: '38134958'
    type: []
    version: null
  relation: []
  toolType:
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  topic:
  - term: Genotype and phenotype
    uri: http://edamontology.org/topic_0625
  - term: Plant biology
    uri: http://edamontology.org/topic_0780
  - term: Sequencing
    uri: http://edamontology.org/topic_3168
  - term: DNA polymorphism
    uri: http://edamontology.org/topic_2885
  - term: Structural variation
    uri: http://edamontology.org/topic_3175
  validated: 0
  version: []
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