Modeling biochemical pathways in the gene ontology
Author(s) -
David P. Hill,
Peter D’Eustachio,
Tanya Berardini,
Chris Mungall,
Nikolai Renedo,
Judith A. Blake
Publication year - 2016
Publication title -
database
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.406
H-Index - 62
ISSN - 1758-0463
DOI - 10.1093/database/baw126
Subject(s) - ontology , computer science , representation (politics) , biological pathway , computational biology , gene ontology , annotation , knowledge representation and reasoning , data science , information retrieval , gene , artificial intelligence , biology , genetics , philosophy , gene expression , epistemology , politics , political science , law
The concept of a biological pathway, an ordered sequence of molecular transformations, is used to collect and represent molecular knowledge for a broad span of organismal biology. Representations of biomedical pathways typically are rich but idiosyncratic presentations of organized knowledge about individual pathways. Meanwhile, biomedical ontologies and associated annotation files are powerful tools that organize molecular information in a logically rigorous form to support computational analysis. The Gene Ontology (GO), representing Molecular Functions, Biological Processes and Cellular Components, incorporates many aspects of biological pathways within its ontological representations. Here we present a methodology for extending and refining the classes in the GO for more comprehensive, consistent and integrated representation of pathways, leveraging knowledge embedded in current pathway representations such as those in the Reactome Knowledgebase and MetaCyc. With carbohydrate metabolic pathways as a use case, we discuss how our representation supports the integration of variant pathway classes into a unified ontological structure that can be used for data comparison and analysis.
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