瞿佳

博士、讲师

常州大学计算机与人工智能学院
阿里云大数据学院
江苏常州213164

E-MAIL:






教育背景:

2017.09-2020.06 中国矿业大学 信息与控制工程学院 控制理论与控制工程专业 工学博士
2014.09-2017.07 安徽师范大学 数学计算机科学学院 生物数学专业 理学硕士
2010.09-2014.07 淮北师范大学 数学科学学院 数学与应用数学专业 理学学士

工作履历:

2020.09-至今 常州大学 人工智能专业 教师

学术兼职:

担任Scientific Reports (影响因子: 3.998)、Current Genomics (影响因子: 2.63)、BMC Systems Biology (影响因子: 2.048)、IEEE Transactions on NanoBioscience (影响因子: 2.791)、Oncology Letter (影响因子: 1.482)、IEEE Journal of Biomedical and Health Informatics(影响因子: 5.223)杂志审稿人。

主授课程:

本科生课程：


研究生课程：

研究领域:

计算生物信息学

奖励与荣誉:

学术成果:

· 教材与专著

此处粘贴出版的教材与专著
· 发表论文

（1）Jia Qu, Xing Chen*, Jun Yin, Yan Zhao, Zheng-Wei Li. Prediction of potential miRNA-Disease associations using matrix decomposition and label propagation. Knowledge-Based Systems. 2019, 186: 104963.(SCI, 影响因子: 5.921，中科院一区)
（2）Jia Qu, Xing Chen*, Ya-Zhou Sun, Yan Zhao, Shu-Bin Cai, Zhong Ming*, Zhu-Hong You*, Jian-Qiang Li. In Silico Prediction of Small Molecule-miRNA Associations Based on the HeteSim Algorithm. Molecular Therapy-Nucleic Acids.2019, 14: 274-286. (SCI，影响因子: 7.032，中科院二区)
（3）Jia Qu, Xing Chen*, Ya-Zhou Sun, Jian-Qiang Li, Zhong Ming. Inferring potential small molecule-miRNA association based on triple layer heterogeneous network. Journal of Cheminformatics. 2018, 10: 30. (SCI, 影响因子5.318，中科院二区)
（4）Jia Qu, Yan Zhao*, Jun Yin. Identification and Analysis of Human Microbe-Disease Associations by Matrix Decomposition and Label Propagation. Frontiers in Microbiology. 2019, 10: 291.(SCI, 影响因子: 4.235，中科院二区)
（5）Jia Qu, Yan Zhao, Li Zhang, Chunchun Wang^*. Computational Models for Self-Interacting Proteins Prediction. Protein & Peptide Letters.（SCI, 影响因子1.156, 中科院四区)
（6）Bin-Sheng He, Jia Qu*, Min Chen*. Prediction of potential disease-associated microRNAs by composite network based inference. Scientific Reports. 2018, 8(1): 15813. (SCI, 影响因子: 3.998, 中科院三区)
（7）Bin-Sheng He, Jia Qu*, Qi Zhao*. Identifying and Exploiting Potential miRNA-Disease Associations with Neighborhood Regularized Logistic Matrix Factorization. Frontiers in Genetics. 2018, 9: 303. (SCI, 影响因子: 3.258, 中科院二区)
（8）Xing Chen*, Jia Qu, Jun Yin. TLHNMDA: Triple Layer Heterogeneous Network Based Inference for MiRNA-Disease Association prediction. Frontiers in Genetics. 2018, 9: 234. (SCI, 影响因子: 3.258, 中科院二区)
（9）Xing Chen*, Lei Wang, Jia Qu, Na-Na Guan, Jian-Qiang Li. Predicting miRNA-disease association based on inductive matrix completion. Bioinformatics. 2018, 34(24): 4256-4265. (SCI, 影响因子: 5.610, 中科院二区)
（10）Xing Chen*, Jun Yin, Jia Qu, Li Huang. MDHGI: Matrix Decomposition and Heterogeneous Graph Inference for miRNA-disease association prediction. PLoS Computational Biology. 2018, 14(8): e**. (SCI, 影响因子: 4.700, 中科院二区)
（11）Chun-Chun Wang, Xing Chen*, Jia Qu, Ya-Zhou Sun, Jian-Qiang Li. RFSMMA: A New Computational Model to Identify and Prioritize Potential Small Molecule–MiRNA Associations. Journal of Chemical Information and Modeling. 2019, 59(4): 1668-1679. (SCI, 影响因子: 4.549，中科院二区)
（12）Chun-Chun Wang, Xing Chen*, Jun Yin, Jia Qu. An integrated framework for the identification of potential miRNA-disease association based on novel negative samples extraction strategy. RNA Biology. 2019, 16(3): 257-269. (SCI, 影响因子: 5.350，中科院二区)
（13）Yan Zhao, Xing Chen*, Jun Yin, Jia Qu. SNMFSMMA: using symmetric nonnegative matrix factorization and Kronecker regularized least squares to predict potential small molecule-microRNA association. RNA Biology. 2019, 59(4): 1668-1679.（SCI，影响因子5.350, 中科院二区）
（14）Dongqing Guo, Colin E. Murdoch, Tianhua Liu, Jia Qu, Shihong Jiao, Yong Wang*, Wei Wang*, Xing Chen*. Therapeutic Angiogenesis of Chinese Herbal Medicines in Ischemic Heart Disease: A Review. Frontiers in Pharmacology. 2018, 9: 428. (SCI, 影响因子: 4.225, 中科院二区)
（15）Xing Chen*, Ya-Zhou Sun, Na-Na Guan, Jia Qu, Zhi-An Huang, Ze-Xuan Zhu, Jian-Qiang Li. Computational models for lncRNA function prediction and functional similarity calculation. Briefings in Functional Genomics. 2019, 18(1): 58-82. (SCI, 影响因子: 2.941, 中科院二区)
（16）Xing Chen*, Na-Na Guan, Ya-Zhou Sun, Jian-Qiang Li*, Jia Qu. MicroRNA-small molecule association identification: from experimental results to computational models. Briefings in Bioinformatics. 2020, 21(1), 47-61. (SCI, 影响因子: 8.990, 中科院一区)



研究项目:

（1）国家自然科学基金重点项目，**，基于图与组合优化的生物数据和网络数据挖掘算法研究，2020.01-2024.12，270万，在研，参加
（2） 国家自然科学基金面上项目，**，基于多源数据融合的药物响应和药物相关非编码RNA靶点预测研究，2020.01-2023.12，60万，在研，参加
（3） 国家自然科学基金面上项目，**，多视角识别长非编码RNA和人类复杂疾病关联预测研究，16万，结题，参加