Unifying the identification of biomedical entities with the Bioregistry

Charles Tapley Hoyt, Meghan Balk, Tiffany J. Callahan, Daniel Domingo-Fernández, Melissa A. Haendel, Harshad B. Hegde, Daniel S. Himmelstein, Klas Karis, John Kunze, Tiago Lubiana, Nicolas Matentzoglu, Julie McMurry, Sierra Moxon, Christopher J. Mungall, Adriano Rutz, Deepak R. Unni, Egon Willighagen, Donald Winston, Benjamin M. Gyori

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

The standardized identification of biomedical entities is a cornerstone of interoperability, reuse, and data integration in the life sciences. Several registries have been developed to catalog resources maintaining identifiers for biomedical entities such as small molecules, proteins, cell lines, and clinical trials. However, existing registries have struggled to provide sufficient coverage and metadata standards that meet the evolving needs of modern life sciences researchers. Here, we introduce the Bioregistry, an integrative, open, community-driven metaregistry that synthesizes and substantially expands upon 23 existing registries. The Bioregistry addresses the need for a sustainable registry by leveraging public infrastructure and automation, and employing a progressive governance model centered around open code and open data to foster community contribution. The Bioregistry can be used to support the standardized annotation of data, models, ontologies, and scientific literature, thereby promoting their interoperability and reuse. The Bioregistry can be accessed through https://bioregistry.io and its source code and data are available under the MIT and CC0 Licenses at https://github.com/biopragmatics/bioregistry.

Original languageEnglish (US)
Article number714
JournalScientific Data
Volume9
Issue number1
DOIs
StatePublished - Dec 2022
Externally publishedYes

ASJC Scopus subject areas

  • Statistics and Probability
  • Information Systems
  • Education
  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Library and Information Sciences

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