ArticleBriefings in bioinformatics2026
ToxiCompass: an evidence-tracked benchmark for short-peptide toxicity screening and confidence-aware assay prioritization.
Article in Briefings in bioinformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Abstract
Binary peptide-toxicity predictors support early screening but do not indicate which assays should follow a toxin-like prediction. We present ToxiCompass, an evidence-tracked benchmark and two-stage protocol for short-peptide toxicity screening and assay-family prioritization. The benchmark contains 6114 peptides reconstructed from online database of biotoxins and reviewed Universal Protein Knowledgebase records, including curated toxin-positive peptides and length-matched operational comparators. Among 2866 Stage 2 candidate toxin-positive peptides, 2858 retained at least one observed-positive target/effect-family label after evidence review. Exact-sequence merging, provenance tracking, Many-against-Many sequence searching 2 clustering at 90% sequence identity (MMSeqs90) cluster-level splitting, and explicit evidence rules define the evaluation. Stage 1 assigns a toxin-like score relative to the operational-comparator population, whereas Stage 2 ranks 13 broad target/effect families to prioritize follow-up assays for toxin-positive peptides with retained evidence. On the primary MMSeqs90 cluster split, Stage 1 achieved an area under the receiver operating characteristic curve of 0.9871 and an area under the precision-recall curve of 0.9867, while Stage 2 achieved a Hit@3 of 0.8955. In a more conservative grouped-split sensitivity analysis, Stage 2 Hit@3 was 0.6506. Together, these results support ToxiCompass as a reproducible benchmark linking toxin-like peptide screening with evidence-aware prioritization of follow-up assay families.
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