|Jie Zheng, Associate Professor|
Tel: (021) 20684861
Healthcare Big Data
Jie Zheng is currently the SMIRC Director and the Recruitment and Admissions Committee Director.
Jie Zheng received his B.Eng degree (honors) in Computer Science from Zhejiang University in 2000, and Ph.D. in Computer Science from the University of California, Riverside in 2006. From Aug. 2006 to Feb. 2011, he was a postdoctoral visiting fellow and research scientist at National Center for Biotechnology Information (NCBI), National Library of Medicine (NLM), National Institutes of Health (NIH), USA. After that, he worked as an Assistant Professor at the School of Computer Science and Engineering, Nanyang Technological University (NTU), Singapore. From Oct. 2012, he was also an Adjunct Senior Research Scientist at Genome Institute of Singapore (GIS), A*STAR, Singapore. In June 2018, Dr. Zheng joined ShanghaiTech University as an Associate Professor.
Dr. Zheng has published more than 50 journal papers (14 of which have impact factors higher than 5) and over 40 conference papers. He has served as PC member and reviewer for a number of international conferences, and as Program Co-Chair for two conferences. Moreover, he reviews many papers for top-tier journals (e.g. Bioinformatics, Nucleic Acids Research) each year. In Singapore, Dr. Zheng was PI of 3 competitive external research grants at national level (with total funding more than 2 millions Singapore dollars), and he participated in more than 10 other projects as Co-PI or collaborator. In the iGEM (International Genetically Engineered Machine Competition) 2015, Dr. Zheng was the coach of mathematical modeling for the NTU team of students, who won a gold medal. At InCoB (International Conference on Bioinformatics) 2017, he won a best paper award (gold medal) in BMC track. In 2016 and 2017, Dr. Zheng was nominated for the Nanyang Education Award at NTU.
Ket Hing Chong, Sandhya Samarasinghe, Don Kulasiri*, Jie Zheng, “Mathematical modelling of core regulatory mechanism in p53 protein that activates apoptotic switch”, Journal of Theoretical Biology, vol. 462, pp. 134-147, February 2019 (IF = 1.833).
Yong Liu, Min Wu*, Chenghao Liu, Xiao-Li Li, Jie Zheng, “SL2MF: Predicting synthetic lethality in human cancers via Logistic Matrix Factorization”, IEEE/ACM Transactions on Computational Biology and Bioinformatics(TCBB), in press, 2019 (IF= 2.428).
Haifen Chen, Devamuni A.K. Maduranga, Piyushkumar Mundra, Jie Zheng, “Bayesian data fusion of gene expression and histone modification profiles for inference of gene regulatory network”, IEEE/ACM Transactions on Computational Biology and Bioinformatics(TCBB), PP(99):1, 2019 (IF= 2.428)
Lichun Ma, Jie Zheng, “Single-cell gene expression data analysis reveals beta-cell dysfunction and deficit mechanisms in type 2 diabetes”, BMC Bioinformatics, vol. 19(Suppl 19), p. 515, 2018 (special issue of GIW 2018) (IF=2.213).
Jing Guo, Jie Zheng, “HopLand: Single-cell pseudotime recovery using continuous Hopfield network based modeling of Waddington’s epigenetic landscape”, Bioinformatics, vol. 33, no. 14, pp. i102 – i109 (special issue of flagship conference ISMB/ECCB 2017, acceptance rate 16.5%), 2017 (IF= 7.307).
Lichun Ma, Jie Zheng, “A polynomial based model for cell fate prediction in human diseases”, BMC Systems Biology, vol. 11(Suppl 7), pp. 126, 2017 (Best Paper Award, Gold Medal, the 16th International Conference on Bioinformatics (InCoB 2017)).
Jing Guo, Feng Lin, Xiaomeng Zhang, Vivek Tanavde, Jie Zheng, “NetLand: quantitative modeling and visualization of Waddington’s epigenetic landscape using probabilistic potential”, Bioinformatics, vol. 33, no. 10, pp. 1583 – 1585, 2017 (IF = 7.307).
Jing Guo, Hui Liu, Jie Zheng, “SynLethDB: synthetic lethality database toward discovery of selective and sensitive anticancer drug targets”, Nucleic Acids Research, vol. 44, no. D1, pp. D1011 – D1017, 2016 (IF = 10.162).
Haifen Chen, Jing Guo, Shital K Mishra, Paul Robson, Mahesan Niranjan, Jie Zheng, “Single-cell transcriptional analysis to uncover regulatory circuits driving cell fate decisions in early mouse development”, Bioinformatics, vol. 31, no. 7, pp. 1060 – 1066, 2015 (IF = 7.307).
Jian-Ping Mei, Chee-Keong Kwoh, Peng Yang, Xiao-Li Li, Jie Zheng, “Drug-Target Interaction Prediction by Learning from Local Information and Neighbors”, Bioinformatics, vol. 29, no. 2, pp. 238-245, 2013 (IF = 7.307).