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[21] Gopalakrishnan, Chandrasekhar,Xu, Caixia,Han, Pengyong,Ramalingam, Rajasekaran,李政伟.Delineating QSAR Descriptors to Explore the Inherent Properties of Naturally Occurring Polyphenols, Responsible for Alpha-Synuclein Amyloid Disaggregation Scheming Towards Effective Therapeutics Against Parkinson’s Disorder,2021,v 12838 LNAI,p231-241
[22] Dong, Yuan,Xu, Caixia,Ren, Chenxia,Han, Pengyong,Ren, Fei,李政伟,Wei, Zibai.Study on the Mechanism of Cistanche in the Treatment of Colorectal Cancer Based on Network Pharmacology,2021,v 12838 LNAI,p242-252
[23] 李佳树,李政伟,聂茹,尤著宏,鲍文正.FCGCNMDA: predicting miRNA-disease associations by applying fully connected graph convolutional networks,2020,卷: 295期: 5页: 1197-1209
[24] Li, Hao-Yuan,You, Zhu-Hong,李政伟,Zhou, Ji-Ren,Hu, Peng-Wei.A Network Embedding-Based Method for Predicting miRNA-Disease Associations by Integrating Multiple Information,2020,v 12465 LNAI,p367-377
[25] Ren, Chenxia,Han, Pengyong,Gopalakrishnan, Chandrasekhar,Xu, Caixia,Ramalingam, Rajasekaran,李政伟.Expression and Gene Regulation Network of ELF3 in Breast Invasive Carcinoma Based on Data Mining,2020,v 12464 LNCS,p514-523
[26] Zhang, ChengYong,李政伟,聂茹,王雷,Zhao, Huan.Image Classification Based on Deep Belief Network and YELM,2020,v 12463 LNCS,p150-159
[27] 李政伟,聂茹,尤著宏,曹晨,李佳树.Using discriminative vector machine model with 2DPCA to predict interactions among proteins,2019,20(supp)
[28] 瞿佳,陈兴,殷俊,赵岩,李政伟.Prediction of potential miRNA-disease associations using matrix decomposition and label propagation,2019,v 186,
[29] Bao, Wenzheng,Yang, Bin,Li, Dan,李政伟,周勇,Bao, Rong.CMSENN: Computational Modification Sites with Ensemble Neural Network,2019,卷: 185页: 65-72
[30] 李政伟,聂茹,You, Zhuhong,赵艳,葛欣,Wang, Yang.LRMDA: Using Logistic Regression and Random Walk with Restart for MiRNA-Disease Association Prediction,2019,v 11644 LNCS,p283-293

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