HNEDTI: Prediction of drug-target interaction based on heterogeneous network embedding. - Zhangli Lu; Yake Wang; Min Zeng; Min Li 007 (BIBM, 2019)

LncRNA-disease association prediction through combining linear and non-linear features with matrix factorization and deep learning techniques. - Min Zeng; Chengqian Lu; Fuhao Zhang; Zhangli Lu; Fang-Xiang Wu; Yaohang Li; Min Li 007 (BIBM, 2019)

NEDD: a network embedding based method for predicting drug-disease associations. - Renyi Zhou; Zhangli Lu; Huimin Luo; Ju Xiang; Min Zeng; Min Li 007 (BMC Bioinform., 2020)

BACPI: a bi-directional attention neural network for compound-protein interaction and binding affinity prediction. - Min Li 007; Zhangli Lu; Yifan Wu 008; Yaohang Li (Bioinform., 2022)

DTIAM: A unified framework for predicting drug-target interactions, binding affinities and activation/inhibition mechanisms. - Zhangli Lu; Chuqi Lei; Kaili Wang; Libo Qin 001; Jing Tang 002; Min Li 007 (CoRR, 2023)

StackCPA: A stacking model for compound-protein binding affinity prediction based on pocket multi-scale features. - Chuqi Lei; Zhangli Lu; Meng Wang; Min Li 007 (Comput. Biol. Medicine, 2023)