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.
@article{arxiv.2212.13543,
title = {Democratising Knowledge Representation with BioCypher},
author = {Sebastian Lobentanzer and Patrick Aloy and Jan Baumbach and Balazs Bohar and Pornpimol Charoentong and Katharina Danhauser and Tunca Doğan and Johann Dreo and Ian Dunham and Adrià Fernandez-Torras and Benjamin M. Gyori and Michael Hartung and Charles Tapley Hoyt and Christoph Klein and Tamas Korcsmaros and Andreas Maier and Matthias Mann and David Ochoa and Elena Pareja-Lorente and Ferdinand Popp and Martin Preusse and Niklas Probul and Benno Schwikowski and Bünyamin Sen and Maximilian T. Strauss and Denes Turei and Erva Ulusoy and Judith Andrea Heidrun Wodke and Julio Saez-Rodriguez},
journal= {arXiv preprint arXiv:2212.13543},
year = {2023}
}
Comments
34 pages, 6 figures; submitted to Nature Biotechnology