iRice-MS: An integrated XGBoost model for detecting multitype post-translational modification sites in rice. - Hao Lv; Yang Zhang 125; Jia-Shu Wang; Shi-Shi Yuan; Zi-Jie Sun; Fu-Ying Dao; Zheng-Xing Guan; Hao Lin 001; Ke-Jun Deng (Briefings Bioinform., 2022)

iPADD: A Computational Tool for Predicting Potential Antidiabetic Drugs Using Machine Learning Algorithms. - Xiao-Wei Liu; Tian-Yu Shi; Dong Gao 002; Cai-Yi Ma; Hao Lin 001; Dan Yan; Ke-Jun Deng (J. Chem. Inf. Model., 2023)

Predicting coronary heart disease in Chinese diabetics using machine learning. - Cai-Yi Ma; Yamei Luo; Tian-Yu Zhang; Yu-Duo Hao; Xue-Qin Xie; Xiao-Wei Liu; Xiaolei Ren 003; Xiaolin He; Yu-Mei Han; Ke-Jun Deng; Dan Yan; Hui Yang; et al. (Comput. Biol. Medicine, 2024)

EDS-Kcr: deep supervision based on large language model for identifying protein lysine crotonylation sites across multiple species. - Hong-Qi Zhang; Xin-Ran Lin; Yan-Ting Wang; Wen-Fang Pei; Guang-Ji Ma; Ze-Xu Zhou; Ke-Jun Deng; Dan Yan; Tian-Yuan Liu (Briefings Bioinform., 2025)