HGMDA: HyperGraph for Predicting MiRNA-Disease Association. - Qing-Wen Wu; Yu-Tian Wang; Zhen Gao; Ming-Wen Zhang; Jian-Cheng Ni 001; Chun-Hou Zheng 001 (ICIC (2), 2019)

Graph regularized L2, 1-nonnegative matrix factorization for miRNA-disease association prediction. - Zhen Gao; Yu-Tian Wang; Qing-Wen Wu; Jian-Cheng Ni 001; Chun-Hou Zheng 001 (BMC Bioinform., 2020)

GAERF: predicting lncRNA-disease associations by graph auto-encoder and random forest. - Qing-Wen Wu; Jun-Feng Xia; Jian-Cheng Ni 001; Chun-Hou Zheng 001 (Briefings Bioinform., 2021)

AEMDA: inferring miRNA-disease associations based on deep autoencoder. - Cunmei Ji; Zhen Gao; Xu Ma; Qing-Wen Wu; Jian-Cheng Ni 001; Chunhou Zheng 001 (Bioinform., 2021)

MiRNA-disease association prediction via hypergraph learning based on high-dimensionality features. - Yu-Tian Wang; Qing-Wen Wu; Zhen Gao; Jian-Cheng Ni 001; Chun-Hou Zheng 001 (BMC Medical Informatics Decis. Mak., 2021)

A New Method Based on Matrix Completion and Non-Negative Matrix Factorization for Predicting Disease-Associated miRNAs. - Zhen Gao; Yu-Tian Wang; Qing-Wen Wu; Lei Li; Jian-Cheng Ni 001; Chun-Hou Zheng 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

Extra Trees Method for Predicting LncRNA-Disease Association Based On Multi-Layer Graph Embedding Aggregation. - Qing-Wen Wu; Rui-Fen Cao; Jun-Feng Xia; Jian-Cheng Ni 001; Chunhou Zheng 001; Yan-Sen Su (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

A Retrieval-Based Molecular Style Transformation Optimization Model. - Cheng Wang; Ya-Jie Zhang; Xin Xia; Yan-Sen Su; Chun-Hou Zheng 001; Qing-Wen Wu (ICIC (LNBI 1), 2024)