Wei Lu, M.S., Ph.D.

626-218-2975
Wei Lu​ Member David Chen Lab
Postdoctoral Fellow, Department of Systems Biology
Research Area
Development of Methods for Designing and Predicting Drug-target Binding and Ligand Binding Areas
Algorithms for Cancer Epigenetics-related Information Analysis
Regulatory Network Analysis
Research Teams
Systems Biology
Wei Lu, Ph.D., M.S., is a postdoctoral fellow in the David Chen Lab in the Department of Systems Biology. He received his Ph.D. and M.S. degree in informatics (computer science) at Kyoto University, Japan, and B.S. in software engineering from Dalian Jiaotong University, China. Before joining the City of Hope, Dr. Lu worked as a research assistant in developing novel methods for analyzing metabolic networks and predicting protein structures at Kyoto University, Japan. He also joined the research projects of traffic information systems supported by the Japanese government at the National Institute of Informatics, Japan. Currently, his research focuses on creating novel computational methods to support the development of diagnostics and therapeutics. Dr. Lu wants to develop cutting-edge computer technology to serve our patients.
Education & Experience
Degrees

  • 2015, Ph.D., Informatics (Computer Science), Kyoto University, Kyoto, Japan

  • 2011, M.S., Informatics (Computer Science), Kyoto University, Kyoto, Japan

  • 2004, B.S., Software Engineering, Dalian Jiaotong University, Liaoning, China

Professional Experience

  • 2019-present, Postdoctoral Fellow, Department of Systems Biology, Beckman Research Institute of City of Hope, Duarte, CA

  • 2015-2017, Postdoctoral Fellow, Digital Content and Media Sciences Research, National Institute of Informatics, Tokyo, Japan

Publications
Tamura T, Lu W, Song J, Akutsu T. Computing Minimum Reaction Modifications in a Boolean Metabolic Network. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2018; 15(6): 1853-62.
 
Alegre-Sanahuja J, Lu W,  Takasu A. Wavelet Transform Based Vehicle Detection from Sensors for Bridge Weigh-in-Motion. The 31st Annual ACM Symposium on Applied Computing (SAC2016). 2016; 935-940.
 
Tamura T, Lu W, Akutsu T. Computational Methods for Modification of Metabolic Networks. Computational and Structural Biotechnology Journal. 2015; 13: 376-81.
 
Lu W, Tamura T, Song J, Akutsu T. Computing Smallest Intervention Strategies for Multiple Metabolic Networks in a Boolean Model. Journal of Computational Biology. 2015; 22(2): 85-110.
 
Lu W, Tamura T, Song J, Akutsu T. Integer programming-based method for designing synthetic metabolic networks by minimum reaction insertion in a Boolean model. PLoS ONE. 2014; 9: e92637.