arXiv:2212.13543

Democratising Knowledge Representation with BioCypher

Sebastian Lobentanzer, Patrick Aloy, Jan Baumbach, Balazs Bohar, Pornpimol Charoentong, Katharina Danhauser, Tunca Doğan, Johann Dreo, Ian Dunham, Adrià Fernandez-Torras, Benjamin M. Gyori, Michael Hartung, Charles Tapley Hoyt, Christoph Klein, Tamas Korcsmaros 외 14명

제출 2022-12-27

원문 초록

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.

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