Adaptive total-variation joint learning model for analyzing single cell RNA seq data. - Dai-Jun Zhang; Jing-Xiu Zhao; Jin-Xing Liu 001; Ying-Lian Gao (BIBM, 2021)

A new framework for drug-disease association prediction combing light-gated message passing neural network and gated fusion mechanism. - Bao-Min Liu; Ying-Lian Gao; Dai-Jun Zhang; Feng Zhou 021; Juan Wang 003; Chun-Hou Zheng 001; Jin-Xing Liu 001 (Briefings Bioinform., 2022)

Spatial Domain Identification Based on Graph Attention Denoising Auto-encoder. - Yue Gao; Dai-Jun Zhang; Cui-Na Jiao; Ying-Lian Gao; Jin-Xing Liu 001 (ICIC (3), 2023)

Non-Negative Low-Rank Representation With Similarity Correction for Cell Type Identification in scRNA-Seq Data. - Jin-Xing Liu 001; Dai-Jun Zhang; Jing-Xiu Zhao; Chun-Hou Zheng 001; Ying-Lian Gao (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

A New Graph Autoencoder-Based Consensus-Guided Model for scRNA-seq Cell Type Detection. - Dai-Jun Zhang; Ying-Lian Gao; Jing-Xiu Zhao; Chun-Hou Zheng 001; Jin-Xing Liu 001 (IEEE Trans. Neural Networks Learn. Syst., 2024)