Protein Ontology (PRO): enhancing and scaling up the representation of protein entities. Issue Volume 45:Issue D1(2017) (28th November 2016)

• Record Type: Journal Article
• Authors: Natale, Darren A.; Arighi, Cecilia N.; Blake, Judith A.; Bona, Jonathan; Chen, Chuming; Chen, Sheng-Chih; Christie, Karen R.; Cowart, Julie; D'Eustachio, Peter; Diehl, Alexander D.; Drabkin, Harold J.; Duncan, William D.; Huang, Hongzhan; Ren, Jia; Ross, Karen; Ruttenberg, Alan; Shamovsky, Veronica; Smith, Barry; Wang, Qinghua; Zhang, Jian; El-Sayed, Abdelrahman; Wu, Cathy H.
• Is Part Of: Nucleic acids research. Volume 45:Issue D1(2017)
• Page Start: D339
• Page End: D346
• Publication Date: 2016-11-28
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gkw1075
• Languages: English
• ISSNs: 0305-1048

Abstract

Abstract: The Protein Ontology (PRO; http://purl.obolibrary.org/obo/pr ) formally defines and describes taxon-specific and taxon-neutral protein-related entities in three major areas: proteins related by evolution; proteins produced from a given gene; and protein-containing complexes. PRO thus serves as a tool for referencing protein entities at any level of specificity. To enhance this ability, and to facilitate the comparison of such entities described in different resources, we developed a standardized representation of proteoforms using UniProtKB as a sequence reference and PSI-MOD as a post-translational modification reference. We illustrate its use in facilitating an alignment between PRO and Reactome protein entities. We also address issues of scalability, describing our first steps into the use of text mining to identify protein-related entities, the large-scale import of proteoform information from expert curated resources, and our ability to dynamically generate PRO terms. Web views for individual terms are now more informative about closely-related terms, including for example an interactive multiple sequence alignment. Finally, we describe recent improvement in semantic utility, with PRO now represented in OWL and as a SPARQL endpoint. These developments will further support the anticipated growth of PRO and facilitate discoverability of and allow aggregation of data relating to protein entities.