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

被引：26

作者：

Breit, Anna ^{[1
]}

Ott, Simon ^{[1
]}

Agibetov, Asan ^{[1
]}

Samwald, Matthias ^{[1
]}

机构：

[1] Med Univ Vienna, Ctr Med Stat Informat & Intelligent Syst, Sect Artificial Intelligence & Decis Support, A-1090 Vienna, Austria

来源：

BIOINFORMATICS | 2020年 / 36卷 / 13期

基金：

欧盟地平线“2020”;

关键词：

D O I：

10.1093/bioinformatics/btaa274

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

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.

引用

页码：4097 / 4098

页数：2

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