OpenBioLink: a benchmarking framework for large-scale biomedical link prediction

Abstract Summary Recently, novel machine-learning algorithms have shown potential for predicting undiscovered links in biomedical knowledge networks. However, dedicated benchmarks for measuring algorithmic progress have not yet emerged. With OpenBioLink, we introduce a large-scale, high-quality and...

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Bibliographic Details
Published in:Bioinformatics 2020-07, Vol.36 (13), p.4097-4098
Main Authors: Breit, Anna, Ott, Simon, Agibetov, Asan, Samwald, Matthias
Format: Article
Language:English
Subjects:
Algorithms
Benchmarking
Machine Learning
Software
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Summary:Abstract Summary Recently, novel machine-learning algorithms have shown potential for predicting undiscovered links in biomedical knowledge networks. However, dedicated benchmarks for measuring algorithmic progress have not yet emerged. With OpenBioLink, we introduce a large-scale, high-quality and highly challenging biomedical link prediction benchmark to transparently and reproducibly evaluate such algorithms. Furthermore, we present preliminary baseline evaluation results. Availability and implementation Source code and data are openly available at https://github.com/OpenBioLink/OpenBioLink. Supplementary information Supplementary data are available at Bioinformatics online.
ISSN:1367-4803
1460-2059
1367-4811
DOI:10.1093/bioinformatics/btaa274