Benchmark Radar
AI BENCHMARK PROFILE

AMPBench-MT

Health & Life SciencesSafety & TrustworthinessZihengZhou06

AMPBench-MT evaluates antimicrobial peptide prediction across binary recognition, species-conditioned potency regression, and endpoint-specific safety readouts (hemolysis, toxicity, selectivity) under a sequence-homology-controlled protocol. It includes 13 source databases and multiple task configurations.

Released
2026-07-28
Readiness
Inspectable
Primary field
Health & Life Sciences

Why it matters

Existing AMP benchmarks focus on binary recognition, but follow-up decisions need assay-derived evidence. AMPBench-MT provides a joint evaluation with homology-controlled splits to reveal that high binary performance does not guarantee assay-endpoint behavior.

Motivation

Computational AMP discovery is often evaluated through AMP/non-AMP recognition, yet follow-up decisions depend on assay-derived evidence such as target-species potency, hemolysis, toxicity, and selectivity.

Primary resources

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