OpenBioLink
A resource and evaluation framework for benchmarking link prediction models on large-scale, heterogeneous biomedical knowledge graphs.
What is OpenBioLink?
OpenBioLink is a resource and evaluation framework designed for benchmarking link prediction models on heterogeneous biomedical knowledge graphs. It provides large-scale, openly available datasets and standardized tools to create custom benchmarks and evaluate model performance, addressing the need for reproducible and fair comparisons in biomedical graph machine learning.
Researchers and data scientists working on biomedical knowledge graph completion, link prediction, and graph machine learning, particularly those needing standardized benchmarks for model evaluation.
Developers choose OpenBioLink for its comprehensive, large-scale benchmark datasets that minimize information leakage, include true negative edges, and support heterogeneous graphs, along with its open-source evaluation framework that ensures reproducibility and comparability across studies.
Overview
OpenBioLink is a resource and evaluation framework for evaluating link prediction models on heterogeneous biomedical graph data.
Use Cases
Best For
- Benchmarking new link prediction algorithms on biomedical data
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