GATSBI: Improving context-aware protein embeddings through biologically motivated data splits
Abstract
GATSBI, a framework for learning protein embeddings using Graph Attention Networks (GATs) and biologically informed data splits. The learned embeddings are evaluated across multiple downstream biological tasks, including interaction prediction, function prediction, and pathway-level inference.
Fields of Study & Subjects
Machine Learning in Bioinformatics
Bioinformatics and Genomic Networks
Advanced Graph Neural Networks
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 22 January 2026
- Document type
- Dataset