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Reactome and the Gene Ontology: digital convergence of data resources

Good, Benjamin M. and Van Auken, Kimberly and Hill, David P. and Mi, Huaiyu and Carbon, Seth and Balhoff, James P. and Albou, Laurent-Philippe and Thomas, Paul D. and Mungall, Christopher J. and Blake, Judith A. and D’Eustachio, Peter (2021) Reactome and the Gene Ontology: digital convergence of data resources. Bioinformatics, 37 (19). pp. 3343-3348. ISSN 1367-4803. PMCID PMC8504636. doi:10.1093/bioinformatics/btab325.

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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.

Item Type:Article
Related URLs:
URLURL TypeDescription CentralArticle
Good, Benjamin M.0000-0002-7757-3347
Van Auken, Kimberly0000-0002-1706-4196
Hill, David P.0000-0002-7326-2509
Mi, Huaiyu0000-0001-8721-202X
Carbon, Seth0000-0001-8244-1536
Balhoff, James P.0000-0002-8688-6599
Albou, Laurent-Philippe0000-0001-5801-1974
Thomas, Paul D.0000-0002-9074-3507
Mungall, Christopher J.0000-0002-6601-2165
Blake, Judith A.0000-0001-8522-334X
D’Eustachio, Peter0000-0002-5494-626X
Additional Information:© The Author(s) 2021. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. Received: 23 December 2020; Revision received: 18 March 2021; Editorial decision: 19 April 2021; Accepted: 27 April 2021; Published: 08 May 2021. This work was supported by grants from the National Institutes of Health [U41 HG02273 to support the GO Consortium; U41 HG 003751 to support the Reactome Knowledgebase], and by funds from the Director, Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy [Contract No. DE-AC02-05CH11231 to C.J.M. and S.C.]. Conflict of Interest: none declared.
Funding AgencyGrant Number
NIHU41 HG02273
NIHU41 HG 003751
Department of Energy (DOE)DEAC02-05CH11231
Issue or Number:19
PubMed Central ID:PMC8504636
Record Number:CaltechAUTHORS:20210513-141147825
Persistent URL:
Official Citation:Benjamin M Good, Kimberly Van Auken, David P Hill, Huaiyu Mi, Seth Carbon, James P Balhoff, Laurent-Philippe Albou, Paul D Thomas, Christopher J Mungall, Judith A Blake, Peter D’Eustachio, Reactome and the Gene Ontology: digital convergence of data resources, Bioinformatics, Volume 37, Issue 19, 1 October 2021, Pages 3343–3348,
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:109122
Deposited By: Tony Diaz
Deposited On:13 May 2021 21:39
Last Modified:15 Oct 2021 15:58

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