paper.md

title	tags	authors	affiliations	date	paper_url
Democratizing knowledge representation with BioCypher	Bioinformatics Knowledge Representation Computational Biology Software	name affiliation corresponding Sebastian Lobentanzer 1 true name affiliation Patrick Aloy 2 3 name affiliation Jan Baumbach 4 name affiliation Balazs Bohar 5 6 name affiliation Vincent J. Carey 7 name affiliation Pornpimol Charoentong 8 9 name affiliation Katharina Danhauser 10 name affiliation Tunca Doğan 11 12 name affiliation Johann Dreo 13 14 name affiliation Ian Dunham 15 16 name affiliation Elias Farr 1 name affiliation Adrià Fernandez-Torras 2 name affiliation Benjamin M. Gyori 17 name affiliation Michael Hartung 4 name affiliation Charles Tapley Hoyt 17 name affiliation Christoph Klein 10 name affiliation Tamas Korcsmaros 5 18 19 name affiliation Andreas Maier 4 name affiliation Matthias Mann 20 21 name affiliation David Ochoa 15 16 name affiliation Elena Pareja-Lorente 2 name affiliation Ferdinand Popp 22 name affiliation Martin Preusse 23 name affiliation Niklas Probul 4 name affiliation Benno Schwikowski 13 name affiliation Bünyamin Sen 11 12 name affiliation Maximilian T. Strauss 20 name affiliation Denes Turei 1 name affiliation Erva Ulusoy 11 12 name affiliation Dagmar Waltemath 24 name affiliation Judith A. H. Wodke 24 name affiliation corresponding Julio Saez-Rodriguez 1 true	name index Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Bioquant 1 name index Institute for Research in Biomedicine (IRB Barcelona), the Barcelona Institute of Science and Technology 2 name index Institució Catalana de Recerca i Estudis Avançats (ICREA) 3 name index Institute for Computational Systems Biology, University of Hamburg, Germany 4 name index Earlham Institute, Norwich, UK 5 name index Biological Research Centre, Szeged, Hungary 6 name index Channing Division of Network Medicine, Mass General Brigham, Harvard Medical School, Boston, USA 7 name index Centre for Quantitative Analysis of Molecular and Cellular Biosystems (Bioquant), Heidelberg University 8 name index Department of Medical Oncology, National Centre for Tumour Diseases (NCT), Heidelberg University Hospital (UKHD) 9 name index Department of Pediatrics, Dr. von Hauner Children’s Hospital, University Hospital, LMU Munich, Germany 10 name index Biological Data Science Lab, Department of Computer Engineering, Hacettepe University, Ankara, Turkey 11 name index Department of Bioinformatics, Graduate School of Health Sciences, Hacettepe University, Ankara, Turkey 12 name index Computational Systems Biomedicine Lab, Department of Computational Biology, Institut Pasteur, Université Paris Cité, Paris, France 13 name index Bioinformatics and Biostatistics Hub, Institut Pasteur, Université Paris Cité, Paris, France 14 name index European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK 15 name index Open Targets, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK 16 name index Laboratory of Systems Pharmacology, Harvard Medical School, Boston, USA 17 name index Imperial College London, London, UK 18 name index Quadram Institute Bioscience, Norwich, UK 19 name index Proteomics Program, Novo Nordisk Foundation Centre for Protein Research, University of Copenhagen, Copenhagen, Denmark 20 name index Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany 21 name index Applied Tumour Immunity Clinical Cooperation Unit, National Centre for Tumour Diseases (NCT), German Cancer Research Centre (DKFZ), Im Neuenheimer Feld 460, 69120, Heidelberg, Germany 22	2023-06-19	https://doi.org/10.1038/s41587-023-01848-y

Statement of need

Building a knowledge graph for biomedical tasks usually takes months or years, often requiring a team of experts in knowledge representation, ontology engineering, and software development. This is a major bottleneck for biomedical research, as it prevents researchers from quickly building knowledge graphs for their specific research questions. We propose BioCypher, a knowledge graph construction tool that democratises knowledge representation by enabling biomedical researchers to build knowledge graphs more easily.

Summary

BioCypher is an open-source Python framework built around the concept of a “threefold modularity”: modularity of data sources, modularity of structure-giving ontology, and modularity of output formats. This design allows for a high degree of flexibility and reusability, rationalising efforts by leveraging the biomedical community.

References

For all references, see the paper.