Drug repositioning offers an efficient alternative to de novo drug development; however, accurately identifying potential drug-disease associations remains challenging. Existing methods do not fully exploit higher-order collaborative information at the drug-drug and disease-disease levels, and their feature fusion stra...
Hao Zhang, Jin-Can Li, Xian-Fang Tang et al.· Journal of Chemical Informat...· 0 citations
Predicting drug synergy is essential for optimizing combination therapies in cancer treatment. Under extreme data scarcity, existing computational methods struggle to generalize to new cell lines. Although meta-learning approaches have shown promise, a critical limitation lies in their reliance on a unimodal Gaussian p...
Shuting Jin, Xu Guo, Anqi Huang et al.· Proceedings of the 32nd ACM...· 0 citations
GoMA-DTA is proposed, a framework integrating gene ontology (GO) functional annotations with protein semantic features with channelwise gating mechanism that uses functional semantics as anchors to dynamically recalibrate ESM-2embeddings, achieving adaptive semantic filtering.
An Xiong, Zheyu Zhou, Ya-Zi Li et al.· IEEE Transactions on Neural...· 0 citations
MultiGeo is a DTA prediction framework that explicitly leverages multiple protein conformations rather than a single snapshot, and introduces a disagreement-aware gating mechanism that adaptively fuses this ensemble representation with the dominant structure only when the additional conformers provide complementary inf...
Rui-Da Zeng, Cheng Guo, Ya-Jie Meng et al.· Proceedings of the Thirty-Fi...· 0 citations
Accurate prediction of drug-target binding affinity (DTA) is a key task in virtual screening. However, current computational methods face a key challenge: sequence-based approaches often fail to capture critical spatial information, while structure-based models rely on computationally expensive 3D coordinates, which re...
Junlin Xu, Ye Yuan, Menglong Hu et al.· IEEE journal of biomedical a...· 0 citations
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