PepBenchmark unifies 35 peptide datasets in 7 groups, a standardized preprocessing pipeline, and a leaderboard with baselines across fingerprint, GNN, PLM, and SMILES models to enable comparable peptide ML research.
For MMseqs2-based homology splitting, parameter settings also need to be standardized
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PepBenchmark: A Standardized Benchmark for Peptide Machine Learning
PepBenchmark unifies 35 peptide datasets in 7 groups, a standardized preprocessing pipeline, and a leaderboard with baselines across fingerprint, GNN, PLM, and SMILES models to enable comparable peptide ML research.