Reliable evaluation of antimicrobial peptide (AMP) predictors is complicated by train-test sequence-similarity leakage and mismatched comparisons with strong protein language model baselines. We present a leakage-controlled framework that quantifies auxiliary-modality value through zero-initialized residual corrections...
Ming-Jian Zhang, Guo-Dong Li, Ying Chang et al.· IEEE transactions on computa...· 0 citations
Herb–disease association prediction is central to computational traditional medicine, but existing graph and hypergraph methods mainly rely on observed topology and underuse biomedical textual semantics, especially in heterogeneous or sparse association networks.
We propose LLM-H2G, a biomedical semantic...
Jun Zhang, Hengchuang Yin, Chao Wu et al.· BMC Bioinformatics· 0 citations
Large language models (LLMs) have significantly revolutionized natural language processing through their strong capabilities in text generation and reasoning. Yet, their applicability to bioinformatics applications remains largely unexplored. Here, we systematically evaluate state‐of‐the‐art LLMs across six represent...
Hengchuang Yin, Zi-Wen Cui, Dong-Xu Li et al.· Advanced Computing· 0 citations
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