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, data and supplementary files are openly available at https://github.com/OpenBioLink/OpenBioLink CONTACT: matthias.samwald ((at)) meduniwien.ac.at
@article{arxiv.1912.04616,
title = {OpenBioLink: A benchmarking framework for large-scale biomedical link prediction},
author = {Anna Breit and Simon Ott and Asan Agibetov and Matthias Samwald},
journal= {arXiv preprint arXiv:1912.04616},
year = {2022}
}