• English
  • Deutsch
  • Log In
    Password Login
    Research Outputs
    Fundings & Projects
    Researchers
    Institutes
    Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Artikel
  4. Unifying the identification of biomedical entities with the Bioregistry
 
  • Details
  • Full
Options
November 19, 2022
Journal Article
Title

Unifying the identification of biomedical entities with the Bioregistry

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.
Author(s)
Hoyt, Charles
Balk, Meghan
Callahan, Tiffany J.
Domingo Fernández, Daniel  
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
Haendel, Melissa A.
Hegde, Harshad B.
Himmelstein, Daniel S.
Karis, Klas
Kunze, John
Lubiana, Tiago
Matentzoglu, Nicolas
McMurry, Julie
Moxon, Sierra
Mungall, Christopher J.
Rutz, Adriano
Unni, Deepak
Willighagen, Egon
Winston, Donald
Gyori, Benjamin
Journal
Scientific data  
Open Access
DOI
10.1038/s41597-022-01807-3
10.24406/publica-601
File(s)
s41597-022-01807-3.pdf (1.88 MB)
Rights
CC BY 4.0: Creative Commons Attribution
Language
English
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Contact
© 2024