Fields
Pick a domain and keep going deeper: field, subfield, topic. Every step lists the papers at that point or below it. The counts are papers that are accepted or in review; papers that were not accepted are in the full library.
Field
Machine learning for biology (proteins, genomics, single-cell, drug discovery)
Computational biology ML covers structure prediction and design of proteins, sequence models of proteins and DNA used for fitness and variant-effect prediction, representation learning on single-cell omics, and prediction of molecular properties and drug-target interactions. Evaluation is dominated by curated community benchmarks with held-out families, time splits or scaffold splits (CASP / CAMEO, ProteinGym, scIB, Therapeutics Data Commons), because random splits leak homology and inflate results; simple baselines are frequently competitive and must be shown.