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Yelu Jiang

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Open access Aug 2026

iDCF: Interpretable deconvolution of cell fractions via biologically-informed deep learning using scRNA-seq data.

iDCF (Interpretable Deconvolution of Cell Fractions) is a novel framework that enforces biological topology onto deep neural networks, bridging the gap between computational inference and biological intuition.

Hongming Guo, Tingfang Wu, Wen-Zheng Wang et al. · 0 citations
Jul 2026

A Structure-Aware Multimodal Framework for Drug–Target Interaction Prediction via Heterogeneous Graph Learning

Predicting drug–target interactions is critical for drug discovery, yet many deep learning methods overlook atom–residue–level relationships, so PHGDTI is proposed, a multimodal framework that integrates sequence and structural cues for binding prediction.

Hua Qian, Deng Pan, Liangpeng Nie et al. · 0 citations