Leakage-aware multi-evidence framework for predicting human gene druggability. Integrates 22 biological feature blocks, 8 druggability targets, and 440 Random Forest/XGBoost benchmark datasets for systematic therapeutic target prioritisation.
machine-learning bioinformatics genomics computational-biology drug-discovery target-prioritization drug-target-discovery gene-druggability
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Updated
Jun 14, 2026 - Python