Dr. Lei Xie is currently an associate professor in Computer Science at Hunter College, and Ph.D. program in Computer Science, Biology and Biochemistry in the City University of New York. His research focuses on developing new data mining, biophysics, and systems biology methods for multi-scale modeling of causal genotype-phenotype associations and drug actions, and applying to drug discovery for complex diseases. From 2004 to 2011, he was a principle scientist at San Diego Supercomputer Center (SDSC). Prior to his stint at SDSC, he worked in pharmaceutical companies Roche and Eidogen to develop enterprise platform for drug discovery. He was trained in Computational Biology as a postdoctoral fellow at Prof. Barry Honig’s group in Columbia University and Howard Hughes Medical Institute. He obtained his Ph.D. in Organic Chemistry and M.S. in Computer Science from Rutgers University, and B.S. in Polymer Physics from University of Science and Technology of China.

Contact Information

Lei Xie, PhD
Associate Professor
Hunter College
Phone : 619.347.7483
Contact Via Email

Department: Computer Science


  • Data Science
  • Biophysics
  • Systems Biology

Research Title

Biological data mining, structural systems pharmacology, precision medicine

Brief Description of Research

My primary research interest is to develop and apply novel computational techniques for understanding genetic, molecular and cellular mechanisms of complex diseases such as cancer, Alzheimer’s disease, and drug-resistant bacterial infection, and drug actions in their treatment. The ultimate goal is to rationally design safe and potent precision medicines. My research approaches include the development of new data mining algorithms and the integration of big data analysis with mechanism-based modeling and simulation (e.g. biophysics and systems biology).

Publications pertaining to the HPC over the past five years

Z.H. Ni, A. C. Yuksel, X.Y. Ni, M. I. Mandel, L. Xie (2017) "Confused or not Confused? Disentangling Brain Activity from EEG Data Using Bidirectional LSTM Recurrent Neural Networks". ACM-BCB'17. Boston, MA, USA

A. Wang, H. Lim, S.-Y. Cheng, L. Xie (2017) "ANTENNA, a Multi-Rank, Multi-Layered Recommender System for Inferring Reliable Drug-Gene-Disease Associations: Repurposing Diazoxide as a Targeted Anti-Cancer Therapy". BioKDD'17. Halifax, Canada

J. Ji, D. He, Y. Feng, Y. He, F. Xue, L. Xie (2017) "JDINAC: joint density-based non-parametric differential interaction network analysis and classification using high-dimensional sparse omics data". Bioinformatics. 2017 Jun 5. doi: 10.1093/bioinformatics/btx360. [Epub ahead of print] 

H.-S. Lim, A. Poleksic, Y. Yao, H. Tong, L. Zhuang, P. Meng, L. Xie (2016) "Large scale off-target prediction using an accurate and efficient one-class collaborative filtering algorithm and its application to drug repurposing". PLoS Comp Biol. 12(10):e1005135

C. Ng, Y. Zhang, P. E. Bourne & L. Xie (2014) "Anti-infectious Drug Repurposing Using an Integrated Chemical Genomics and Structural Systems Biology Approach", Pacific Symposium on Biocomputing, 19:136-47

Current Funding

Anti-infectious drug discovery using structural systems pharmacology: This application proposes to apply a novel structural systems pharmacology approach to discovering new therapeutics to combat drug-resistant bacteria.
Role: Principal investigator   

NIH R01LM011986                 L. Xie (PI)   09/01/14 – 08/31/18 
Drug discovery by integrating chemical genomics and structural systems biology: The goal of this proposal is to develop novel computational methods to predict high-resolution proteome-scale drug-target interactions and apply them to anti-infectious drug repurposing. 
Role: Principal investigator

Collaborators on the HPCC based Research Project

Jia Xu, Computer Science, Hunter College

Contribution of the HPC in my research

Molecular modeling
Large-scale computation
Algorithm development