CA-DEL is a new multi-target benchmark for training ML models on noisy DEL sequencing data and evaluating them on high-fidelity Ki binding affinities from ChEMBL to address selectivity among homologous carbonic anhydrase isoforms.
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CA-DEL: An Open Multi-Target, Multi-Modal Benchmark for Learning from DNA-Encoded Library Screens
CA-DEL is a new multi-target benchmark for training ML models on noisy DEL sequencing data and evaluating them on high-fidelity Ki binding affinities from ChEMBL to address selectivity among homologous carbonic anhydrase isoforms.