Democratising Knowledge Representation with BioCypher

Standardising the representation of biomedical knowledge among all researchers is an insurmountable task, hindering the effectiveness of many computational methods. To facilitate harmonisation and interoperability despite this fundamental challenge, we propose to standardise the framework of knowled...

Full description

Saved in:
Bibliographic Details
Published in:arXiv.org 2023-01
Main Authors: Lobentanzer, Sebastian, Aloy, Patrick, Baumbach, Jan, Bohar, Balazs, Charoentong, Pornpimol, Danhauser, Katharina, Tunca Doğan, Dreo, Johann, Dunham, Ian, Fernandez-Torras, Adrià, Gyori, Benjamin M, Hartung, Michael, Charles Tapley Hoyt, Klein, Christoph, Korcsmaros, Tamas, Maier, Andreas, Mann, Matthias, Ochoa, David, Pareja-Lorente, Elena, Popp, Ferdinand, Preusse, Martin, Probul, Niklas, Schwikowski, Benno, Sen, Bünyamin, Strauss, Maximilian T, Turei, Denes, Ulusoy, Erva, Judith Andrea Heidrun Wodke, Saez-Rodriguez, Julio
Format: Article
Language:English
Subjects:
Accessibility
Graphs
Interoperability
Knowledge representation
Standardization
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Standardising the representation of biomedical knowledge among all researchers is an insurmountable task, hindering the effectiveness of many computational methods. To facilitate harmonisation and interoperability despite this fundamental challenge, we propose to standardise the framework of knowledge graph creation instead. We implement this standardisation in BioCypher, a FAIR (findable, accessible, interoperable, reusable) framework to transparently build biomedical knowledge graphs while preserving provenances of the source data. Mapping the knowledge onto biomedical ontologies helps to balance the needs for harmonisation, human and machine readability, and ease of use and accessibility to non-specialist researchers. We demonstrate the usefulness of this framework on a variety of use cases, from maintenance of task-specific knowledge stores, to interoperability between biomedical domains, to on-demand building of task-specific knowledge graphs for federated learning. BioCypher (https://biocypher.org) frees up valuable developer time; we encourage further development and usage by the community.
ISSN:2331-8422