count: 5
list:
- accessibility: null
  additionDate: '2017-03-30T21:27:31Z'
  biotoolsCURIE: biotools:gdr
  biotoolsID: gdr
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Contact Form
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://www.rosaceae.org/contact
  description: Contains all publically available Rosaceae sequences including annotated
    peach, strawberry and almond EST sequences and the genetically anchored peach
    physical map.
  documentation:
  - note: null
    type:
    - User manual
    url: https://www.rosaceae.org/userManual
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Mapping
      uri: http://edamontology.org/operation_2429
    - term: Sequence tagged site (STS) mapping
      uri: http://edamontology.org/operation_2871
    - term: Genetic mapping
      uri: http://edamontology.org/operation_0282
    - term: EST assembly
      uri: http://edamontology.org/operation_0526
    - term: Physical mapping
      uri: http://edamontology.org/operation_2944
    output: []
  homepage: http://www.rosaceae.org/
  homepage_status: 0
  language:
  - Perl
  lastUpdate: '2024-11-24T20:31:42.764457Z'
  license: null
  link: []
  maturity: null
  name: Genome Database for Rosaceae (GDR)
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID:
  - type: rrid
    value: RRID:SCR_012756
    version: null
  owner: ELIXIR-EE
  publication:
  - doi: 10.1186/1471-2105-5-130
    metadata:
      abstract: 'Background: Peach is being developed as a model organism for Rosaceae,
        an economically important family that includes fruits and ornamental plants
        such as apple, pear, strawberry, cherry, almond and rose. The genomics and
        genetics data of peach can play a significant role in the gene discovery and
        the genetic understanding of related species. The effective utilization of
        these peach resources, however, requires the development of an integrated
        and centralized database with associated analysis tools. Description: The
        Genome Database for Rosaceae (GDR) is a curated and integrated web-based relational
        database. GDR contains comprehensive data of the genetically anchored peach
        physical map, an annotated peach EST database, Rosaceae maps and markers and
        all publicly available Rosaceae sequences. Annotations of ESTs include contig
        assembly, putative function, simple sequence repeats, and anchored position
        to the peach physical map where applicable. Our integrated map viewer provides
        graphical interface to the genetic, transcriptome and physical mapping information.
        ESTs, BACs and markers can be queried by various categories and the search
        result sites are linked to the integrated map viewer or to the WebFPC physical
        map sites. In addition to browsing and querying the database, users can compare
        their sequences with the annotated GDR sequences via a dedicated sequence
        similarity server running either the BLAST or FASTA algorithm. To demonstrate
        the utility of the integrated and fully annotated database and analysis tools,
        we describe a case study where we anchored Rosaceae sequences to the peach
        physical and genetic map by sequence similarity. Conclusions: The GDR has
        been initiated to meet the major deficiency in Rosaceae genomics and genetics
        research, namely a centralized web database and bioinformatics tools for data
        storage, analysis and exchange. GDR can be accessed at http://www.genome.clemson.edu/gdr/.
        © 2004 Jung et al; licensee BioMed Central Ltd.'
      authors:
      - name: Jung S.
      - name: Jesudurai C.
      - name: Staton M.
      - name: Du Z.
      - name: Ficklin S.
      - name: Cho I.
      - name: Abbott A.
      - name: Tomkins J.
      - name: Main D.
      citationCount: 86
      date: '2004-09-09T00:00:00Z'
      journal: BMC Bioinformatics
      title: 'GDR (Genome Database for Rosaceae): Integrated web resources for Rosaceae
        genomics and genetics research'
    note: null
    pmcid: PMC517928
    pmid: '15357877'
    type: []
    version: null
  - doi: 10.1093/nar/gkm803
    metadata:
      abstract: The Genome Database for Rosaceae (GDR) is a central repository of
        curated and integrated genetics and genomics data of Rosaceae, an economically
        important family which includes apple, cherry, peach, pear, raspberry, rose
        and strawberry. GDR contains annotated databases of all publicly available
        Rosaceae ESTs, the genetically anchored peach physical map, Rosaceae genetic
        maps and comprehensively annotated markers and traits. The ESTs are assembled
        to produce unigene sets of each genus and the entire Rosaceae. Other annotations
        include putative function, microsatellites, open reading frames, single nucleotide
        polymorphisms, gene ontology terms and anchored map position where applicable.
        Most of the published Rosaceae genetic maps can be viewed and compared through
        CMap, the comparative map viewer. The peach physical map can be viewed using
        WebFPC/WebChrom, and also through our integrated GDR map viewer, which serves
        as a portal to the combined genetic, transcriptome and physical mapping information.
        ESTs, BACs, markers and traits can be queried by various categories and the
        search result sites are linked to the mapping visualization tools. GDR also
        provides online analysis tools such as a batch BLAST/FASTA server for the
        GDR datasets, a sequence assembly server and microsatellite and primer detection
        tools. GDR is available at http://www.rosaceae.org. © 2007 The Author(s).
      authors:
      - name: Jung S.
      - name: Staton M.
      - name: Lee T.
      - name: Blenda A.
      - name: Svancara R.
      - name: Abbott A.
      - name: Main D.
      citationCount: 177
      date: '2008-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'GDR (Genome Database for Rosaceae): Integrated web-database for Rosaceae
        genomics and genetics data'
    note: null
    pmcid: PMC2238863
    pmid: '17932055'
    type: []
    version: null
  relation: []
  toolType:
  - Database portal
  topic:
  - term: Mapping
    uri: http://edamontology.org/topic_0102
  - term: Gene transcripts
    uri: http://edamontology.org/topic_3512
  - term: DNA polymorphism
    uri: http://edamontology.org/topic_2885
  - term: Physics
    uri: http://edamontology.org/topic_3318
  - term: Genetic variation
    uri: http://edamontology.org/topic_0199
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-08-20T15:59:14Z'
  biotoolsCURIE: biotools:tassel
  biotoolsID: tassel
  collectionID:
  - Animal and Crop Genomics
  confidence_flag: null
  cost: null
  credit:
  - email: tassel@googlegroups.com
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Software package to evaluate traits associations, evolutionary patterns,
    and linkage disequilibrium.
  documentation:
  - note: null
    type:
    - User manual
    url: https://bitbucket.org/tasseladmin/tassel-5-source/wiki/UserManual
  download: []
  editPermission:
    authors:
    - animalandcropgenomics
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Linkage analysis
      uri: http://edamontology.org/operation_0283
    - term: Linkage disequilibrium calculation
      uri: http://edamontology.org/operation_0488
    output: []
  homepage: http://www.maizegenetics.net/tassel
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2024-11-24T20:23:52.165977Z'
  license: LGPL-2.1
  link: []
  maturity: null
  name: TASSEL
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID:
  - type: rrid
    value: RRID:SCR_012837
    version: null
  owner: admin
  publication:
  - doi: 10.1093/bioinformatics/btm308
    metadata:
      abstract: 'Summary: Association analyses that exploit the natural diversity
        of a genome to map at very high resolutions are becoming increasingly important.
        In most studies, however, researchers must contend with the confounding effects
        of both population and family structure. TASSEL (Trait Analysis by aSSociation,
        Evolution and Linkage) implements general linear model and mixed linear model
        approaches for controlling population and family structure. For result interpretation,
        the program allows for linkage disequilibrium statistics to be calculated
        and visualized graphically. Database browsing and data importation is facilitated
        by integrated middleware. Other features include analyzing insertions/deletions,
        calculating diversity statistics, integration of phenotypic and genotypic
        data, imputing missing data and calculating principal components. © 2007 The
        Author(s).'
      authors:
      - name: Bradbury P.J.
      - name: Zhang Z.
      - name: Kroon D.E.
      - name: Casstevens T.M.
      - name: Ramdoss Y.
      - name: Buckler E.S.
      citationCount: 5576
      date: '2007-10-01T00:00:00Z'
      journal: Bioinformatics
      title: 'TASSEL: Software for association mapping of complex traits in diverse
        samples'
    note: null
    pmcid: null
    pmid: '17586829'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  - Desktop application
  topic:
  - term: GWAS study
    uri: http://edamontology.org/topic_3517
  - term: Mapping
    uri: http://edamontology.org/topic_0102
  validated: 1
  version: []
- accessibility: null
  additionDate: '2022-10-28T06:14:49.320630Z'
  biotoolsCURIE: biotools:carrotomics
  biotoolsID: carrotomics
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: philipp.simon@usda.gov
    fundrefid: null
    gridid: null
    name: Philipp W Simon
    note: null
    orcidid: https://orcid.org/0000-0001-6978-6062
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: William R Rolling
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  description: CarrotOmics is an integrated web-based relational database, developed
    to house and integrate genomic, genetic and breeding data for carrot and related
    species. CarrotOmics includes genome assemblies, annotated transcripts, traits,
    maps, and markers being generated and used by carrot researchers.
  documentation:
  - note: null
    type:
    - General
    url: https://www.carrotomics.org/userManual
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Genome assembly
      uri: http://edamontology.org/operation_0525
    - term: Genetic mapping
      uri: http://edamontology.org/operation_0282
    - term: EST assembly
      uri: http://edamontology.org/operation_0526
    - term: Database search
      uri: http://edamontology.org/operation_2421
    - term: Transcriptome assembly
      uri: http://edamontology.org/operation_3258
    output: []
  homepage: https://carrotomics.org/
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-24T15:25:47.005153Z'
  license: Other
  link: []
  maturity: null
  name: CarrotOmics
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Chan019
  publication:
  - doi: 10.1093/database/baac079
    metadata:
      abstract: 'CarrotOmics (https://carrotomics.org/) is a comprehensive database
        for carrot (Daucus carota L.) breeding and research. CarrotOmics was developed
        using resources available at the MainLab Bioinformatics core (https://www.bioinfo.wsu.edu/)
        and is implemented using Tripal with Drupal modules. The database delivers
        access to download or visualize the carrot reference genome with gene predictions,
        gene annotations and sequence assembly. Other genomic resources include information
        for 11 224 genetic markers from 73 linkage maps or genotyping-by-sequencing
        and descriptions of 371 mapped loci. There are records for 1601 Apiales species
        (or subspecies) and descriptions of 9408 accessions from 11 germplasm collections
        representing more than 600 of these species. Additionally, 204 Apiales species
        have phenotypic information, totaling 28 517 observations from 10 041 biological
        samples. Resources on CarrotOmics are freely available, search functions are
        provided to find data of interest and video tutorials are available to describe
        the search functions and genomic tools. CarrotOmics is a timely resource for
        the Apiaceae research community and for carrot geneticists developing improved
        cultivars with novel traits addressing challenges including an expanding acreage
        in tropical climates, an evolving consumer interested in sustainably grown
        vegetables and a dynamic environment due to climate change. Data from CarrotOmics
        can be applied in genomic-assisted selection and genetic research to improve
        basic research and carrot breeding efficiency. Database URL: https://carrotomics.org/'
      authors:
      - name: Rolling W.R.
      - name: Senalik D.
      - name: Iorizzo M.
      - name: Ellison S.
      - name: Van Deynze A.
      - name: Simon P.W.
      citationCount: 9
      date: '2022-01-01T00:00:00Z'
      journal: Database
      title: 'CarrotOmics: A genetics and comparative genomics database for carrot
        (Daucus carota)'
    note: null
    pmcid: PMC9450951
    pmid: '36069936'
    type: []
    version: null
  relation: []
  toolType:
  - Database portal
  - Web application
  topic:
  - term: Mapping
    uri: http://edamontology.org/topic_0102
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  - term: Genotype and phenotype
    uri: http://edamontology.org/topic_0625
  - term: Phylogenetics
    uri: http://edamontology.org/topic_3293
  - term: DNA polymorphism
    uri: http://edamontology.org/topic_2885
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2019-05-19T09:00:19Z'
  biotoolsCURIE: biotools:FunMappOne
  biotoolsID: FunMappOne
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: User-friendly graphical interface that allows to visualize and summarize
    the functional annotations of one or multiple molecular biology experiments at
    once.
  documentation:
  - note: null
    type:
    - User manual
    url: https://usermanual.wiki/Document/UserManual.999755866.pdf
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Enrichment analysis
      uri: http://edamontology.org/operation_3501
    - term: Clustering
      uri: http://edamontology.org/operation_3432
    - term: Expression analysis
      uri: http://edamontology.org/operation_2495
    output: []
  homepage: https://github.com/Greco-Lab/FunMappOne
  homepage_status: 0
  language:
  - R
  lastUpdate: '2020-06-16T10:55:24Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Issue tracker
    url: https://github.com/Greco-Lab/FunMappOne/issues
  maturity: Mature
  name: FunMappOne
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: Ruta
  publication:
  - doi: 10.1186/s12859-019-2639-2
    metadata:
      abstract: '© 2019 The Author(s).Background: Functional annotation of genes is
        an essential step in omics data analysis. Multiple databases and methods are
        currently available to summarize the functions of sets of genes into higher
        level representations, such as ontologies and molecular pathways. Annotating
        results from omics experiments into functional categories is essential not
        only to understand the underlying regulatory dynamics but also to compare
        multiple experimental conditions at a higher level of abstraction. Several
        tools are already available to the community to represent and compare functional
        profiles of omics experiments. However, when the number of experiments and/or
        enriched functional terms is high, it becomes difficult to interpret the results
        even when graphically represented. Therefore, there is currently a need for
        interactive and user-friendly tools to graphically navigate and further summarize
        annotations in order to facilitate results interpretation also when the dimensionality
        is high. Results: We developed an approach that exploits the intrinsic hierarchical
        structure of several functional annotations to summarize the results obtained
        through enrichment analyses to higher levels of interpretation and to map
        gene related information at each summarized level. We built a user-friendly
        graphical interface that allows to visualize the functional annotations of
        one or multiple experiments at once. The tool is implemented as a R-Shiny
        application called FunMappOne and is available at https://github.com/grecolab/FunMappOne.
        Conclusion: FunMappOne is a R-shiny graphical tool that takes in input multiple
        lists of human or mouse genes, optionally along with their related modification
        magnitudes, computes the enriched annotations from Gene Ontology, Kyoto Encyclopedia
        of Genes and Genomes, or Reactome databases, and reports interactive maps
        of functional terms and pathways organized in rational groups. FunMappOne
        allows a fast and convenient comparison of multiple experiments and an easy
        way to interpret results.'
      authors:
      - name: Scala G.
      - name: Serra A.
      - name: Marwah V.S.
      - name: Saarimaki L.A.
      - name: Greco D.
      citationCount: 17
      date: '2019-02-15T00:00:00Z'
      journal: BMC Bioinformatics
      title: 'FunMappOne: A tool to hierarchically organize and visually navigate
        functional gene annotations in multiple experiments'
    note: null
    pmcid: PMC6376640
    pmid: '30767762'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Desktop application
  topic:
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  - term: Ontology and terminology
    uri: http://edamontology.org/topic_0089
  - term: Model organisms
    uri: http://edamontology.org/topic_0621
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2019-07-30T08:54:38Z'
  biotoolsCURIE: biotools:mineXpert
  biotoolsID: mineXpert
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: "mineXpert is a graphical user interface software piece that allows\
    \ the user to:\n- load mass spectrometry data files [ (x,y) text files or mzML\
    \ standard format ] \n- visualize the TIC chromatogram and the intensity=(mz,\
    \ dt) colormap in case of ion mobility mass spectrometry\n- integrate the mass\
    \ data in many different ways and display them, effectively permitting the exploration\
    \ of the mass data in their full depth\n- many other features"
  documentation:
  - note: null
    type:
    - User manual
    url: http://msxpertsuite.org/wiki/pmwiki.php/Main/UserManual
  download:
  - note: null
    type: Downloads page
    url: https://sourcesup.renater.fr/frs/?group_id=3534
    version: null
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode:
  - France
  elixirPlatform:
  - Tools
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format: []
    note: null
    operation:
    - term: Chromatogram visualisation
      uri: http://edamontology.org/operation_3203
    - term: Mass spectrum visualisation
      uri: http://edamontology.org/operation_3694
    - term: Isotopic distributions calculation
      uri: http://edamontology.org/operation_3632
    output:
    - data:
        term: Plot
        uri: http://edamontology.org/data_2884
      format: []
  homepage: http://msxpertsuite.org
  homepage_status: 0
  language: []
  lastUpdate: '2020-06-16T10:55:24Z'
  license: GPL-3.0
  link:
  - note: Main software site
    type:
    - Other
    url: http://msxpertsuite.org
  - note: Publication at the American Chemical Society web site
    type:
    - Other
    url: https://pubs.acs.org/doi/10.1021/acs.jproteome.9b00099
  - note: Pubmed record page
    type:
    - Other
    url: https://www.ncbi.nlm.nih.gov/pubmed/30950277
  maturity: Mature
  name: mineXpert
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID:
  - type: doi
    value: doi:10.1021/acs.jproteome.9b00099
    version: null
  owner: rusconi
  publication:
  - doi: 10.1021/acs.jproteome.9b00099
    metadata:
      abstract: © Copyright 2019 American Chemical Society.Biological mass spectrometry
        mainly comprises three fields of endeavor, namely, proteomics, metabolomics,
        and structural biology. In each of these specialties, the mass spectrometrist
        needs to access MS1 mass spectral data, although not necessarily on the same
        basis. For example, the bottom-up proteomics scientist will occasionally access
        MS1 data to perform data inspection, quality assessments, and quantitation
        measurements, whereas top-down proteomics, structural biology, or metabolomics
        scientists will actually spend most of their time mining profile-mode MS1
        data. Furthermore, the advent of ion mobility-mass spectrometry imposes new
        manners of mass spectral data visualization. An open-source MS1-only mass
        data visualization software for the desktop was developed to allow scientists
        to visualize conventional and drift time mass data. Various mass data integrations
        are possible, allowing a thorough mass spectral data scrutiny. Isotopic cluster
        calculations are easily carried over from the chemical formula up to the display
        of the mass spectrum. Deconvolution of mass peaks can be achieved with a simple
        mouse drag. Flexible reporting of data inspection events and of mining discoveries
        is provided. Very large sparse data sets can be sliced into smaller chunks
        replicating the original data without data loss. Task automation is achieved
        in a JavaScript environment. This project allows users of mass spectrometry
        facilities to inspect and mine their MS1 mass data outside of these facilities
        without having to resort to the closed-source vendor software shipped with
        the instruments. mineXpert requires no proprietary software whatsoever once
        the mass spectrometry data have been converted to mzML. The reference implementation
        is version 5.8.2 or greater. Reference material, a detailed user manual, and
        video tutorials are available at http://www.msxpertsuite.org.
      authors:
      - name: Rusconi F.
      citationCount: 4
      date: '2019-05-03T00:00:00Z'
      journal: Journal of Proteome Research
      title: 'MineXpert: Biological Mass Spectrometry Data Visualization and Mining
        with Full JavaScript Ability'
    note: null
    pmcid: null
    pmid: '30950277'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Script
  - Desktop application
  topic:
  - term: Biochemistry
    uri: http://edamontology.org/topic_3292
  - term: Analytical chemistry
    uri: http://edamontology.org/topic_3370
  - term: Computational chemistry
    uri: http://edamontology.org/topic_3332
  validated: 1
  version: []
next: null
previous: null
