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Unni DR, Moxon SAT, Bada M, Brush M, Bruskiewich R, Caufield JH, Clemons PA, Dancik V, Dumontier M, Fecho K, Glusman G, Hadlock JJ, Harris NL, Joshi A, Putman T, Qin G, Ramsey SA, Shefchek KA, Solbrig H, Soman K, Thessen AE, Haendel MA, Bizon C, Mungall CJ, Acevedo L, Ahalt SC, Alden J, Alkanaq A, Amin N, Avila R, Balhoff J, Baranzini SE, Baumgartner A, Baumgartner W, Belhu B, Brandes M, Brandon N, Burtt N, Byrd W, Callaghan J, Cano MA, Carrell S, Celebi R, Champion J, Chen Z, Chen M, Chung L, Cohen K, Conlin T, Corkill D, Costanzo M, Cox S, Crouse A, Crowder C, Crumbley ME, Dai C, Dančík V, De Miranda Azevedo R, Deutsch E, Dougherty J, Duby MP, Duvvuri V, Edwards S, Emonet V, Fehrmann N, Flannick J, Foksinska AM, Gardner V, Gatica E, Glen A, Goel P, Gormley J, Greyber A, Haaland P, Hanspers K, He K, He K, Henrickson J, Hinderer EW, Hoatlin M, Hoffman A, Huang S, Huang C, Hubal R, Huellas‐Bruskiewicz K, Huls FB, Hunter L, Hyde G, Issabekova T, Jarrell M, Jenkins L, Johs A, Kang J, Kanwar R, Kebede Y, Kim KJ, Kluge A, Knowles M, Koesterer R, Korn D, Koslicki D, Krishnamurthy A, Kvarfordt L, Lee J, Leigh M, Lin J, Liu Z, Liu S, Ma C, Magis A, Mamidi T, Mandal M, Mantilla M, Massung J, Mauldin D, McClelland J, McMurry J, Mease P, Mendoza L, Mersmann M, Mesbah A, Might M, Morton K, Muller S, Muluka AT, Osborne J, Owen P, Patton M, Peden DB, Peene RC, Persaud B, Pfaff E, Pico A, Pollard E, Price G, Raj S, Reilly J, Riutta A, Roach J, Roper RT, Rosenblatt G, Rubin I, Rucka S, Rudavsky‐Brody N, Sakaguchi R, Santos E, Schaper K, Schmitt CP, Schurman S, Scott E, Seitanakis S, Sharma P, Shmulevich I, Shrestha M, Shrivastava S, Sinha M, Smith B, Southall N, Southern N, Stillwell L, Strasser M"M, Su AI, Ta C, Thessen AE, Tinglin J, Tonstad L, Tran‐Nguyen T, Tropsha A, Vaidya G, Veenhuis L, Viola A, Grotthuss M, Wang M, Wang P, Watkins PB, Weber R, Wei Q, Weng C, Whitlock J, Williams MD, Williams A, Womack F, Wood E, Wu C, Xin JK, Xu H, Xu C, Yakaboski C, Yao Y, Yi H, Yilmaz A, Zheng M, Zhou X, Zhou E, Zhu Q, Zisk T. Biolink Model: A universal schema for knowledge graphs in clinical, biomedical, and translational science. Clin Transl Sci 2022; 15:1848-1855. [PMID: 36125173 PMCID: PMC9372416 DOI: 10.1111/cts.13302] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 04/27/2022] [Accepted: 05/02/2022] [Indexed: 12/12/2022] Open
Abstract
Within clinical, biomedical, and translational science, an increasing number of projects are adopting graphs for knowledge representation. Graph‐based data models elucidate the interconnectedness among core biomedical concepts, enable data structures to be easily updated, and support intuitive queries, visualizations, and inference algorithms. However, knowledge discovery across these “knowledge graphs” (KGs) has remained difficult. Data set heterogeneity and complexity; the proliferation of ad hoc data formats; poor compliance with guidelines on findability, accessibility, interoperability, and reusability; and, in particular, the lack of a universally accepted, open‐access model for standardization across biomedical KGs has left the task of reconciling data sources to downstream consumers. Biolink Model is an open‐source data model that can be used to formalize the relationships between data structures in translational science. It incorporates object‐oriented classification and graph‐oriented features. The core of the model is a set of hierarchical, interconnected classes (or categories) and relationships between them (or predicates) representing biomedical entities such as gene, disease, chemical, anatomic structure, and phenotype. The model provides class and edge attributes and associations that guide how entities should relate to one another. Here, we highlight the need for a standardized data model for KGs, describe Biolink Model, and compare it with other models. We demonstrate the utility of Biolink Model in various initiatives, including the Biomedical Data Translator Consortium and the Monarch Initiative, and show how it has supported easier integration and interoperability of biomedical KGs, bringing together knowledge from multiple sources and helping to realize the goals of translational science.
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Affiliation(s)
- Deepak R. Unni
- Genome Biology Unit, European Molecular Biology Laboratory Heidelberg Germany
- Division of Environmental Genomics and Systems Biology Lawrence Berkeley National Laboratory Berkeley California USA
| | - Sierra A. T. Moxon
- Division of Environmental Genomics and Systems Biology Lawrence Berkeley National Laboratory Berkeley California USA
| | - Michael Bada
- Center for Health AI University of Colorado Anschutz Medical Campus Aurora Colorado USA
| | - Matthew Brush
- Center for Health AI University of Colorado Anschutz Medical Campus Aurora Colorado USA
| | | | - J. Harry Caufield
- Division of Environmental Genomics and Systems Biology Lawrence Berkeley National Laboratory Berkeley California USA
| | - Paul A. Clemons
- Chemical Biology and Therapeutics Science Program Broad Institute Cambridge Massachusetts USA
| | - Vlado Dancik
- Chemical Biology and Therapeutics Science Program Broad Institute Cambridge Massachusetts USA
| | - Michel Dumontier
- Institute of Data Science Maastricht University Maastricht The Netherlands
| | - Karamarie Fecho
- Renaissance Computing Institute University of North Carolina at Chapel Hill Chapel Hill North Carolina USA
| | | | | | - Nomi L. Harris
- Division of Environmental Genomics and Systems Biology Lawrence Berkeley National Laboratory Berkeley California USA
| | - Arpita Joshi
- Institute for Systems Biology Seattle Washington USA
| | - Tim Putman
- Center for Health AI University of Colorado Anschutz Medical Campus Aurora Colorado USA
| | - Guangrong Qin
- Institute for Systems Biology Seattle Washington USA
| | - Stephen A. Ramsey
- Department of Biomedical Sciences Oregon State University Corvallis Oregon USA
| | - Kent A. Shefchek
- Center for Health AI University of Colorado Anschutz Medical Campus Aurora Colorado USA
| | | | - Karthik Soman
- Department of Neurology University of California San Francisco San Francisco California USA
| | - Anne E. Thessen
- Center for Health AI University of Colorado Anschutz Medical Campus Aurora Colorado USA
| | - Melissa A. Haendel
- Center for Health AI University of Colorado Anschutz Medical Campus Aurora Colorado USA
| | - Chris Bizon
- Renaissance Computing Institute University of North Carolina at Chapel Hill Chapel Hill North Carolina USA
| | - Christopher J. Mungall
- Division of Environmental Genomics and Systems Biology Lawrence Berkeley National Laboratory Berkeley California USA
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