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Reactome and the Gene Ontology: digital convergence of data resources
MOTIVATION: Gene Ontology Causal Activity Models (GO-CAMs) assemble individual associations of gene products with cellular components, molecular functions and biological processes into causally linked activity flow models. Pathway databases such as the Reactome Knowledgebase create detailed molecula...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8504636/ https://www.ncbi.nlm.nih.gov/pubmed/33964129 http://dx.doi.org/10.1093/bioinformatics/btab325 |
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author | Good, Benjamin M Van Auken, Kimberly Hill, David P Mi, Huaiyu Carbon, Seth Balhoff, James P Albou, Laurent-Philippe Thomas, Paul D Mungall, Christopher J Blake, Judith A D’Eustachio, Peter |
author_facet | Good, Benjamin M Van Auken, Kimberly Hill, David P Mi, Huaiyu Carbon, Seth Balhoff, James P Albou, Laurent-Philippe Thomas, Paul D Mungall, Christopher J Blake, Judith A D’Eustachio, Peter |
author_sort | Good, Benjamin M |
collection | PubMed |
description | MOTIVATION: Gene Ontology Causal Activity Models (GO-CAMs) assemble individual associations of gene products with cellular components, molecular functions and biological processes into causally linked activity flow models. Pathway databases such as the Reactome Knowledgebase create detailed molecular process descriptions of reactions and assemble them, based on sharing of entities between individual reactions into pathway descriptions. RESULTS: To convert the rich content of Reactome into GO-CAMs, we have developed a software tool, Pathways2GO, to convert the entire set of normal human Reactome pathways into GO-CAMs. This conversion yields standard GO annotations from Reactome content and supports enhanced quality control for both Reactome and GO, yielding a nearly seamless conversion between these two resources for the bioinformatics community. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-8504636 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-85046362021-10-13 Reactome and the Gene Ontology: digital convergence of data resources Good, Benjamin M Van Auken, Kimberly Hill, David P Mi, Huaiyu Carbon, Seth Balhoff, James P Albou, Laurent-Philippe Thomas, Paul D Mungall, Christopher J Blake, Judith A D’Eustachio, Peter Bioinformatics Original Papers MOTIVATION: Gene Ontology Causal Activity Models (GO-CAMs) assemble individual associations of gene products with cellular components, molecular functions and biological processes into causally linked activity flow models. Pathway databases such as the Reactome Knowledgebase create detailed molecular process descriptions of reactions and assemble them, based on sharing of entities between individual reactions into pathway descriptions. RESULTS: To convert the rich content of Reactome into GO-CAMs, we have developed a software tool, Pathways2GO, to convert the entire set of normal human Reactome pathways into GO-CAMs. This conversion yields standard GO annotations from Reactome content and supports enhanced quality control for both Reactome and GO, yielding a nearly seamless conversion between these two resources for the bioinformatics community. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2021-05-08 /pmc/articles/PMC8504636/ /pubmed/33964129 http://dx.doi.org/10.1093/bioinformatics/btab325 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Papers Good, Benjamin M Van Auken, Kimberly Hill, David P Mi, Huaiyu Carbon, Seth Balhoff, James P Albou, Laurent-Philippe Thomas, Paul D Mungall, Christopher J Blake, Judith A D’Eustachio, Peter Reactome and the Gene Ontology: digital convergence of data resources |
title | Reactome and the Gene Ontology: digital convergence of data resources |
title_full | Reactome and the Gene Ontology: digital convergence of data resources |
title_fullStr | Reactome and the Gene Ontology: digital convergence of data resources |
title_full_unstemmed | Reactome and the Gene Ontology: digital convergence of data resources |
title_short | Reactome and the Gene Ontology: digital convergence of data resources |
title_sort | reactome and the gene ontology: digital convergence of data resources |
topic | Original Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8504636/ https://www.ncbi.nlm.nih.gov/pubmed/33964129 http://dx.doi.org/10.1093/bioinformatics/btab325 |
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