Benchmark datasets for biomedical knowledge graphs with negative statements

We present a collection of datasets for three relation prediction tasks - protein-protein interaction prediction, gene-disease association prediction and disease prediction - that aim at circumventing the difficulties in building benchmarks for knowledge graphs with negative statements. These datasets include data from two successful biomedical ontologies, Gene Ontology and Human Phenotype Ontology, enriched with negative statements.

本研究提出了一组面向三类关系预测任务的数据集集合，涵盖蛋白质-蛋白质相互作用预测（Protein-Protein Interaction Prediction）、基因-疾病关联预测（Gene-Disease Association Prediction）与疾病预测，旨在克服构建带负语句的知识图谱（Knowledge Graph）基准数据集所面临的难题。该数据集集合源自两类成熟的生物医学本体——基因本体（Gene Ontology）与人类表型本体（Human Phenotype Ontology），并补充了负语句。