count: 1982
list:
- accessibility: null
  additionDate: '2025-04-24T13:00:12.867477Z'
  biotoolsCURIE: biotools:eetl_toolset
  biotoolsID: eetl_toolset
  collectionID:
  - EUCAIM
  confidence_flag: null
  cost: null
  credit: []
  description: 'Modular toolchain for an extensible and customizable ETL pipeline
    that extracts, transforms, and loads clinical data and medical imaging metadata,
    applying dataset-specific mappings to generate outputs compatible with the EUCAIM
    Common Data Model (CDM). Its design aims to minimize manual data preparation efforts
    and facilitate customization and integration with other components, such as data
    quality assurance tools.

    Containerized, currently supports input datasets in CSV, JSON, XLSX.'
  documentation: []
  download: []
  editPermission:
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  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Data formatting
      uri: http://edamontology.org/operation_0335
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Data deposition
      uri: http://edamontology.org/operation_3431
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Format validation
      uri: http://edamontology.org/operation_0336
    output: []
  homepage: https://bahiasoftware.es/home
  homepage_status: 0
  language:
  - Java
  - Python
  lastUpdate: '2025-05-08T09:29:42.363560Z'
  license: Apache-2.0
  link: []
  maturity: Emerging
  name: EUCAIM ETL toolset
  operatingSystem:
  - Linux
  - Windows
  otherID: []
  owner: victorsp
  publication: []
  relation: []
  toolType:
  - Workflow
  - Library
  topic:
  - term: Data identity and mapping
    uri: http://edamontology.org/topic_3345
  - term: Workflows
    uri: http://edamontology.org/topic_0769
  validated: 0
  version:
  - 0.9.1
- accessibility: Open access
  additionDate: '2016-07-12T10:54:05Z'
  biotoolsCURIE: biotools:pia
  biotoolsID: pia
  collectionID:
  - KNIME
  - de.NBI
  - Proteomics
  - BioInfra.Prot
  - CUBiMed.RUB
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: julian.uszkoreit@rub.de
    fundrefid: null
    gridid: null
    name: Julian Uszkoreit
    note: null
    orcidid: http://orcid.org/0000-0001-7522-4007
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    - Developer
    - Maintainer
    url: null
  - email: cubimed@rub.de
    fundrefid: null
    gridid: null
    name: CUBiMed.RUB
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  description: The main focus lays on the integrated inference algorithms, concluding
    the proteins from a set of identified spectra. But it also allows you to integrate
    results of various search engines, inspect your peptide spectrum matches, calculate
    FDR values across different results and visualize the correspondence between PSMs,
    peptides and proteins.
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/medbioinf/pia/wiki
  download:
  - note: null
    type: Source code
    url: https://github.com/mpc-bioinformatics/pia
    version: null
  - note: null
    type: Software package
    url: http://bioconda.github.io/recipes/pia/README.html
    version: null
  - note: null
    type: Binaries
    url: https://github.com/mpc-bioinformatics/pia/releases
    version: null
  - note: null
    type: Container file
    url: https://hub.docker.com/r/julianusz/pia
    version: null
  editPermission:
    authors: []
    type: private
  elixirCommunity:
  - Proteomics
  elixirNode:
  - Germany
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Mass spectrometry spectra
        uri: http://edamontology.org/data_0943
      format:
      - term: Mascot .dat file
        uri: http://edamontology.org/format_3713
      - term: mzIdentML
        uri: http://edamontology.org/format_3247
      - term: TSV
        uri: http://edamontology.org/format_3475
      - term: PRIDE XML
        uri: http://edamontology.org/format_3684
      - term: X!Tandem XML
        uri: http://edamontology.org/format_3711
      - term: MSF
        uri: http://edamontology.org/format_3702
      - term: mzTab
        uri: http://edamontology.org/format_3681
    note: PIA allows you to inspect the results of common proteomics spectrum identification
      search engines, combine them seamlessly and conduct statistical analyses. The
      main focus of PIA lays on the integrated inference algorithms, i.e. concluding
      the proteins from a set of identified spectra. But it also allows you to inspect
      your peptide spectrum matches, calculate FDR values across different search
      engine results and visualize the correspondence between PSMs, peptides and proteins.
      Search engine results in several formats peptide spectrum matches (PSMs) and
      peptides Inferred Proteins
    operation:
    - term: Protein identification
      uri: http://edamontology.org/operation_3767
    - term: Target-Decoy
      uri: http://edamontology.org/operation_3649
    output:
    - data:
        term: Peptide identification
        uri: http://edamontology.org/data_0945
      format:
      - term: Sequence feature table format (text)
        uri: http://edamontology.org/format_2206
      - term: KNIME datatable format
        uri: http://edamontology.org/format_3765
      - term: idXML
        uri: http://edamontology.org/format_3764
      - term: TSV
        uri: http://edamontology.org/format_3475
      - term: mzTab
        uri: http://edamontology.org/format_3681
      - term: mzIdentML
        uri: http://edamontology.org/format_3247
    - data:
        term: Protein identifier
        uri: http://edamontology.org/data_0989
      format:
      - term: Sequence feature table format (text)
        uri: http://edamontology.org/format_2206
      - term: KNIME datatable format
        uri: http://edamontology.org/format_3765
      - term: idXML
        uri: http://edamontology.org/format_3764
      - term: TSV
        uri: http://edamontology.org/format_3475
      - term: mzTab
        uri: http://edamontology.org/format_3681
      - term: mzIdentML
        uri: http://edamontology.org/format_3247
  homepage: https://github.com/medbioinf/pia
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2025-05-02T13:15:26.717477Z'
  license: BSD-3-Clause
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/medbioinf/pia
  maturity: Mature
  name: PIA - Protein Inference Algorithms
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: julianu
  publication:
  - doi: 10.1021/acs.jproteome.5b00121
    metadata:
      abstract: Protein inference connects the peptide spectrum matches (PSMs) obtained
        from database search engines back to proteins, which are typically at the
        heart of most proteomics studies. Different search engines yield different
        PSMs and thus different protein lists. Analysis of results from one or multiple
        search engines is often hampered by different data exchange formats and lack
        of convenient and intuitive user interfaces. We present PIA, a flexible software
        suite for combining PSMs from different search engine runs and turning these
        into consistent results. PIA can be integrated into proteomics data analysis
        workflows in several ways. A user-friendly graphical user interface can be
        run either locally or (e.g., for larger core facilities) from a central server.
        For automated data processing, stand-alone tools are available. PIA implements
        several established protein inference algorithms and can combine results from
        different search engines seamlessly. On several benchmark data sets, we show
        that PIA can identify a larger number of proteins at the same protein FDR
        when compared to that using inference based on a single search engine. PIA
        supports the majority of established search engines and data in the mzIdentML
        standard format. It is implemented in Java and freely available at https://github.com/mpc-bioinformatics/pia.
      authors:
      - name: Uszkoreit J.
      - name: Maerkens A.
      - name: Perez-Riverol Y.
      - name: Meyer H.E.
      - name: Marcus K.
      - name: Stephan C.
      - name: Kohlbacher O.
      - name: Eisenacher M.
      citationCount: 57
      date: '2015-07-02T00:00:00Z'
      journal: Journal of Proteome Research
      title: 'PIA: An Intuitive Protein Inference Engine with a Web-Based User Interface'
    note: null
    pmcid: null
    pmid: '25938255'
    type:
    - Primary
    version: null
  - doi: 10.1021/acs.jproteome.8b00723
    metadata:
      abstract: Proteomics using LC-MS/MS has become one of the main methods to analyze
        the proteins in biological samples in high-throughput. But the existing mass-spectrometry
        instruments are still limited with respect to resolution and measurable mass
        ranges, which is one of the main reasons why shotgun proteomics is the major
        approach. Here proteins are digested, which leads to the identification and
        quantification of peptides instead. While often neglected, the important step
        of protein inference needs to be conducted to infer from the identified peptides
        to the actual proteins in the original sample. In this work, we highlight
        some of the previously published and newly added features of the tool PIA
        - Protein Inference Algorithms, which helps the user with the protein inference
        of measured samples. We also highlight the importance of the usage of PSI
        standard file formats, as PIA is the only current software supporting all
        available standards used for spectrum identification and protein inference.
        Additionally, we briefly describe the benefits of working with workflow environments
        for proteomics analyses and show the new features of the PIA nodes for the
        KNIME Analytics Platform. Finally, we benchmark PIA against a recently published
        data set for isoform detection. PIA is open source and available for download
        on GitHub (https://github.com/mpc-bioinformatics/pia) or directly via the
        community extensions inside the KNIME analytics platform.
      authors:
      - name: Uszkoreit J.
      - name: Perez-Riverol Y.
      - name: Eggers B.
      - name: Marcus K.
      - name: Eisenacher M.
      citationCount: 30
      date: '2019-02-01T00:00:00Z'
      journal: Journal of Proteome Research
      title: Protein Inference Using PIA Workflows and PSI Standard File Formats
    note: null
    pmcid: null
    pmid: '30474983'
    type: []
    version: null
  relation:
  - biotoolsID: knime
    type: uses
  toolType:
  - Command-line tool
  - Library
  - Desktop application
  - Workflow
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Protein variants
    uri: http://edamontology.org/topic_3120
  validated: 1
  version:
  - '1.5'
- accessibility: Open access (with restrictions)
  additionDate: '2017-04-22T17:35:18Z'
  biotoolsCURIE: biotools:gemma
  biotoolsID: gemma
  collectionID: []
  confidence_flag: null
  cost: Free of charge (with restrictions)
  credit:
  - email: pavlab-support@msl.ubc.ca
    fundrefid: null
    gridid: null
    name: Pavlidis Lab Support
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Support
    url: https://pavlab.msl.ubc.ca/
  description: Gemma provides data, experimental design annotations, and differential
    expression analysis results for thousands of microarray and RNA-seq experiments.
    We re-analyze raw data from public sources (primarily NCBI GEO), annotate experimental
    conditions, conduct quality control and compute differential expression using
    standardized procedures. We have especially good coverage of experiments relevant
    to the nervous system.
  documentation:
  - note: null
    type:
    - General
    url: https://pavlidislab.github.io/Gemma/
  - note: Documentation for the Gemma REST API.
    type:
    - API documentation
    url: https://gemma.msl.ubc.ca/resources/restapidocs/
  download:
  - note: null
    type: Downloads page
    url: https://github.com/PavlidisLab/Gemma/releases
    version: null
  editPermission:
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    - paulpavlidis
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Gene expression matrix
        uri: http://edamontology.org/data_3112
      format: []
    - data:
        term: Raw microarray data
        uri: http://edamontology.org/data_3110
      format: []
    note: null
    operation:
    - term: Differential gene expression profiling
      uri: http://edamontology.org/operation_3223
    output:
    - data:
        term: Heat map
        uri: http://edamontology.org/data_1636
      format: []
    - data:
        term: Quality control report
        uri: http://edamontology.org/data_3914
      format: []
  homepage: https://gemma.msl.ubc.ca/
  homepage_status: 0
  language:
  - Java
  - JavaScript
  lastUpdate: '2025-04-22T22:09:03.811075Z'
  license: CC-BY-NC-4.0
  link:
  - note: null
    type:
    - Repository
    - Issue tracker
    url: https://github.com/PavlidisLab/Gemma
  maturity: Mature
  name: Gemma
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: artrymix
  publication:
  - doi: 10.1093/bioinformatics/btp259
    metadata:
      abstract: 'Motivation: Many microarray datasets are available online with formalized
        standards describing the probe sequences and expression values. Unfortunately,
        the description, conditions and parameters of the experiments are less commonly
        formalized and often occur as natural language text. This hinders searching,
        high-throughput analysis, organization and integration of the datasets. Results:
        We use the lexical resources and software tools from the Unified Medical Language
        System (UMLS) to extract concepts from text. We then link the UMLS concepts
        to classes in open biomedical ontologies. The result is accessible and clear
        semantic annotations of gene expression experiments. We applied the method
        to 595 expression experiments from Gemma, a resource for re-use and meta-analysis
        of gene expression profiling data. We evaluated and corrected all stages of
        the annotation process. The majority of missed annotations were due to a lack
        of cross-references. The most error-prone stage was the extraction of concepts
        from phrases. Final review of the annotations in context of the experiments
        revealed 89% precision. A naive system, lacking the phrase to concept corrections
        is 68% precise. We have integrated this annotation pipeline into Gemma. ©
        2009 The Author(s).'
      authors:
      - name: French L.
      - name: Lane S.
      - name: Law T.
      - name: Xu L.
      - name: Pavlidis P.
      citationCount: 9
      date: '2009-06-09T00:00:00Z'
      journal: Bioinformatics
      title: Application and evaluation of automated semantic annotation of gene expression
        experiments
    note: null
    pmcid: PMC2687992
    pmid: '19376825'
    type:
    - Primary
    version: null
  - doi: 10.1093/database/baab006
    metadata:
      abstract: 'Vast amounts of transcriptomic data reside in public repositories,
        but effective reuse remains challenging. Issues include unstructured dataset
        metadata, inconsistent data processing and quality control, and inconsistent
        probe-gene mappings across microarray technologies. Thus, extensive curation
        and data reprocessing are necessary prior to any reuse. The Gemma bioinformatics
        system was created to help address these issues. Gemma consists of a database
        of curated transcriptomic datasets, analytical software, a web interface and
        web services. Here we present an update on Gemma''s holdings, data processing
        and analysis pipelines, our curation guidelines, and software features. As
        of June 2020, Gemma contains 10 811 manually curated datasets (primarily human,
        mouse and rat), over 395 000 samples and hundreds of curated transcriptomic
        platforms (both microarray and RNA sequencing). Dataset topics were represented
        with 10 215 distinct terms from 12 ontologies, for a total of 54 316 topic
        annotations (mean topics/dataset = 5.2). While Gemma has broad coverage of
        conditions and tissues, it captures a large majority of available brain-related
        datasets, accounting for 34% of its holdings. Users can access the curated
        data and differential expression analyses through the Gemma website, RESTful
        service and an R package. Database URL: https://gemma.msl.ubc.ca/home.html'
      authors:
      - name: Lim N.
      - name: Tesar S.
      - name: Belmadani M.
      - name: Poirier-Morency G.
      - name: Mancarci B.O.
      - name: Sicherman J.
      - name: Jacobson M.
      - name: Leong J.
      - name: Tan P.
      - name: Pavlidis P.
      citationCount: 21
      date: '2021-01-01T00:00:00Z'
      journal: Database
      title: Curation of over 10 000 transcriptomic studies to enable data reuse
    note: null
    pmcid: PMC7904053
    pmid: '33599246'
    type:
    - Primary
    version: null
  relation:
  - biotoolsID: rsem
    type: uses
  - biotoolsID: multiqc
    type: uses
  - biotoolsID: cutadapt
    type: uses
  - biotoolsID: star
    type: uses
  - biotoolsID: ncbi_geo
    type: uses
  - biotoolsID: sradb
    type: uses
  - biotoolsID: ncbi_gene
    type: uses
  toolType:
  - Web application
  - Web API
  topic:
  - term: RNA-Seq
    uri: http://edamontology.org/topic_3170
  - term: Gene expression
    uri: http://edamontology.org/topic_0203
  - term: Genetics
    uri: http://edamontology.org/topic_3053
  - term: Microarray experiment
    uri: http://edamontology.org/topic_3518
  - term: Data curation and archival
    uri: http://edamontology.org/topic_0219
  validated: 1
  version:
  - 1.31.13
- accessibility: Open access
  additionDate: '2017-04-22T18:19:39Z'
  biotoolsCURIE: biotools:bto
  biotoolsID: bto
  collectionID:
  - DSMZ Digital Diversity
  - de.NBI-biodata
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: contact@brenda-enzymes.org
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Project
    typeRole:
    - Primary contact
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures
    note: null
    orcidid: null
    rorid: 02tyer376
    typeEntity: Institute
    typeRole: []
    url: https://www.dsmz.de/
  description: BRENDA Tissue Ontology is a structured encyclopedia of tissue terms.
    BTO contains different anatomical structures, tissues, cell types and cell lines,
    classified under generic categories corresponding to the rules and formats of
    the Gene Ontology Consortium and organized as a directed acyclic graph (DAG).
    A versatile web interface with several search and navigation functionalities allows
    convenient online access to the BTO and to the enzymes isolated from the tissues.
  documentation:
  - note: null
    type:
    - General
    url: http://www.bto.brenda-enzymes.org/tutorial.php
  download: []
  editPermission:
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    - AJaede
    - juh22
    type: group
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  elixirNode:
  - Germany
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Ontology comparison
      uri: http://edamontology.org/operation_3352
    - term: Gene expression profiling
      uri: http://edamontology.org/operation_0314
    - term: Ontology visualisation
      uri: http://edamontology.org/operation_3559
    output: []
  homepage: http://www.BTO.brenda-enzymes.org
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2025-01-28T08:45:24.895767Z'
  license: CC-BY-4.0
  link:
  - note: null
    type:
    - Other
    url: https://www.dsmz.de/
  - note: null
    type:
    - Service
    url: https://hub.dsmz.de/#/
  - note: BRENDA enzyme  database
    type:
    - Repository
    url: https://www.brenda-enzymes.org/
  maturity: null
  name: The BRENDA Tissue Ontology (BTO)
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: AJaede
  publication:
  - doi: 10.1093/nar/gkq968
    metadata:
      abstract: BTO, the BRENDA Tissue Ontology (http://www.BTO.brenda-enzymes.org)
        represents a comprehensive structured encyclopedia of tissue terms. The project
        started in 2003 to create a connection between the enzyme data collection
        of the BRENDA enzyme database and a structured network of source tissues and
        cell types. Currently, BTO contains more than 4600 different anatomical structures,
        tissues, cell types and cell lines, classified under generic categories corresponding
        to the rules and formats of the Gene Ontology Consortium and organized as
        a directed acyclic graph (DAG). Most of the terms are endowed with comments
        on their derivation or definitions. The content of the ontology is constantly
        curated with ̃1000 new terms each year. Four different types of relationships
        between the terms are implemented. A versatile web interface with several
        search and navigation functionalities allows convenient online access to the
        BTO and to the enzymes isolated from the tissues. Important areas of applications
        of the BTO terms are the detection of enzymes in tissues and the provision
        of a solid basis for text-mining approaches in this field. It is widely used
        by lab scientists, curators of genomic and biochemical databases and bioinformaticians.
        The BTO is freely available at http://www.obofoundry.org. © The Author(s)
        2010.
      authors:
      - name: Gremse M.
      - name: Chang A.
      - name: Schomburg I.
      - name: Grote A.
      - name: Scheer M.
      - name: Ebeling C.
      - name: Schomburg D.
      citationCount: 141
      date: '2011-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'The BRENDA Tissue Ontology (BTO): The first all-integrating ontology
        of all organisms for enzyme sources'
    note: null
    pmcid: PMC3013802
    pmid: '21030441'
    type: []
    version: null
  relation: []
  toolType:
  - Database portal
  topic:
  - term: Ontology and terminology
    uri: http://edamontology.org/topic_0089
  - term: Enzymes
    uri: http://edamontology.org/topic_0821
  - term: Model organisms
    uri: http://edamontology.org/topic_0621
  - term: Biobank
    uri: http://edamontology.org/topic_3337
  - term: Protein targeting and localisation
    uri: http://edamontology.org/topic_0140
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-02-10T11:35:53Z'
  biotoolsCURIE: biotools:assembly_pcr_oligo_maker
  biotoolsID: assembly_pcr_oligo_maker
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: pjohnson@yorku.ac
    fundrefid: null
    gridid: null
    name: Philip E. Johnson
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Assembly PCR Oligo Maker is a tool for designing oligodeoxynucleotides
    for the PCR based construction of long DNA molecules.
  documentation:
  - note: null
    type:
    - User manual
    url: http://www.yorku.ca/pjohnson/oligo/manual.pdf
  download: []
  editPermission:
    authors:
    - xlianghorse
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Virtual PCR
      uri: http://edamontology.org/operation_0307
    - term: Sequence assembly
      uri: http://edamontology.org/operation_0310
    - term: PCR primer design
      uri: http://edamontology.org/operation_0308
    output: []
  homepage: http://www.yorku.ca/pjohnson/AssemblyPCRoligomaker.html
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2025-01-08T15:03:37.029419Z'
  license: null
  link: []
  maturity: null
  name: Assembly PCR Oligo Maker
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: ELIXIR-EE
  publication:
  - doi: 10.1093/nar/gki380
    metadata: null
    note: null
    pmcid: PMC1160141
    pmid: '15980526'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  - term: PCR experiment
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