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.
The hybrid partition combines the advantages of MMseqs2-split and kmer-split, making it a more challenging partitioning strategy
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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.