李雯，女，博士，讲师，中共党员。毕业于湖南大学信息科学与工程学院，获计算机应用工学博士学位。从事人工智能、生物大数据处理的方法理论和应用研究，主要研究方向是基于推荐的预测模型研究，非编码RNA与疾病关联预测，lncRNA-蛋白质交互预测，微生物-药物关联预测，小分子药物靶点预测，机器学习，深度学习等。

联系方式：wenli@hnu.edu.cn，电话：18569503955。

科研成果：

共发表学术论文9篇，其中7篇SCI检索，2篇EI检索。参研了2项科研项目，包括1项国家科学技术部重点研发项目：“基于超级计算的肿瘤大数据分析技术与人工智能诊断标准研究”，1项国家自然科学基金委员会面上项目：“面向自然场景的高效智能感知研究”。

科研论文：

[1]Li W, Wang S, Xu J, Xiang J. Inferring Latent MicroRNA-Disease Associations on a Gene-Mediated Tripartite Heterogeneous Multiplexing Network.IEEE/ACM Trans Comput Biol Bioinforma. 2022;19(6):3190-3201. doi:10.1109/TCBB.2022.3143770

[2]Li W, Wang S, Guo H. LPI-FKLGCN: Predicting LncRNA-Protein Interactions Through Fast Kernel Learning and Graph Convolutional Network. In: Wei Y, Li M, Skums P, Cai Z, eds.Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol 13064 LNBI. Springer International Publishing; 2021:227-238. doi:10.1007/978-3-030-91415-8_20

[3]Li W, Wang S, Xu J. An Ensemble Matrix Completion Model for Predicting Potential Drugs Against SARS-CoV-2.Front Microbiol. 2021;12:1-12. doi:10.3389/fmicb.2021.694534

[4]Liu Y, Wang SL, Zhang JF, Zhang W,Li W. A neural collaborative filtering method for identifying miRNA-disease associations.Neurocomputing. 2021;422:176-185. doi:10.1016/j.neucom.2020.09.032

[5]Liu Y, Wang SL, Zhang JF, Zhang W, Zhou S,Li W. DMFMDA: Prediction of Microbe-Disease Associations Based on Deep Matrix Factorization Using Bayesian Personalized Ranking.IEEE/ACM Trans Comput Biol Bioinforma. 2021;18(5):1763-1772. doi:10.1109/TCBB.2020.3018138

[6]Li W, Wang SL, Xu J, Yang J. Identification of Human LncRNA-Disease Association by Fast Kernel Learning-Based Kronecker Regularized Least Squares. In: Huang D-S, Jo K-H, eds.Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol 12464 LNCS. Springer International Publishing; 2020:302-315. doi:10.1007/978-3-030-60802-6_27

[7]Liu Y, Wang SL, Zhang JF, Zhang W,Li W. LncRNA-disease associations prediction based on neural network-based matrix factorization.IEEE Access. Published online 2020:1. doi:10.1109/ACCESS.2020.2987350

[8]Zhou S, Wang S, Wu Q, Azim R,Li W. Predicting potential miRNA-disease associations by combining gradient boosting decision tree with logistic regression.Comput Biol Chem. 2020;85:107200. doi:10.1016/j.compbiolchem.2020.107200

Li W, Wang S, Xu J, Mao G, Tian G, Yang J. Inferring Latent Disease-lncRNA Associations by Faster Matrix Completion on a Heterogeneous Network.Front Genet. 2019;10. doi:10.3389/fgene.2019.00769