- B.S., University of Science and Technology of China
- M.S., Rutgers University - New Brunswick
- Ph.D., Rutgers University - New Brunswick
Molecular interactions are at the basis of all biological processes. Our research interest is to develop and apply computational techniques to study the structure, function, dynamic, and evolution of molecular interactions on multiple scales, from atomic details to biological networks. The primary goal is to bridge the basic sciences with clinical research through developing and using tools derived from computer science, chemistry, and physics, integrating and analyzing a myriad of omic data, and collaborating with various computational, experimental, and clinical laboratories.
Our immediate aims include i) developing a chemical systems biology-based protein-ligand interaction network analysis framework to model the drug perturbation of biological systems, and bridging structure-based drug design and systems biology to realize systems medicine; ii) genome-scale metabolic modeling of cancer cell to facilitate multi-omic data integration, to reveal oncogenic mutations and functional modules, and to discover biomarkers and new druggable targets for cancer treatments; iii) applying integrated computational techniques to polypharmacology, drug repurposing, and the prediction of drug side effects.
- S. H. Chiu, L. Xie 2014 "Predictive Modeling of Durg Binding and Unbinding Kinetics". PNAS, in preparation.
- C. Chen, H. Tong, L. Xie 2014 "Quantitative Impact of Dynamic Rewiring of Biological Network on Information Dissemination" Mol Sys Biol, in preparation.
- R. Hauptman, C. Ng, T. Hart, L. Xie 2014 "A Generalized Statistical Model for Network Topological Similarity Search and Its Application to Fold Recognition", Bioinformatics, in preparation.
- Y. Zhang, L. Xie, L. Xie & P. E.Bourne 2014 "The Plasmodium falciparum Drugome and its Polypharmacological Implications" PLoS ONE, in preparation.
- L. Xie, X. Ge, H. Tan, L. Xie, Y. Zhang, T. Hart, X. Yan, P. E. Bourne 2014 "Toward Structural Systems Pharmacology to Study Complex Diseases and Personalized Medicine". PLoS Comp Biol, 10(5):e1003554. [PDF]
- 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. [PDF]
- R. Chang, L. Xie, P.E. Bourne, B. Palsson 2013 "Antibacterial mechanisms identified through structural systems pharmacology". BMC Syst. Biol. 7:102 [PDF]
- H. Tan, X. Ge, L. Xie 2013 "Structural systems pharmacology: a new frontier in discovering novel drug targets". Curr Drug Targets, 14:952-956. [Link]
- L. Xie, C. Ng, T. Ali, V. Valencia, B.L. Ferreira, V. Xue, M. Tanweer, D. Zhou, G. Haddad, P. E. Bourne, L. Xie.2013 "Multiscale modeling of the causal functional roles of nsSNPs in a genome-wide association study: application to hypoxia". BMC Genomics 14(S3):S9 [PDF]
- S. L. Epstein, X. Yun, L. Xie L 2013 "Multi-Agent, Multi-Case-Based Reasoning". Lecture Notes in Computer Science, Vol7969: 74-88 [Link]
- G. Daniel, S.L. Kinnings, L. Xie, L. Xie, Y. Zhang, P. E. Bourne, and Y. Gil 2013 "Quantifying Reproducibility in Computational Biology: The Case of the Tuberculosis Drugome". PLoS One 8(11):e80278 [PDF]
- S. Epstein, X. J. Li, P. Valdez, S. Grayevsky, E. Osisek, X. Yun, L. Xie 2012 "Discovering Protein Clusters". AAAI Technical Report FS-12-03, Discovery Informatics: The Role of AI Research in Innovating Scientific Processes. p21-28 [PDF].
- L. Xie, S.L. Kinnings, L. Xie and P.E. Bourne 2012 Predicting the Polypharmacology of Drugs: Identifying New Uses Through Cheminformatics, Structural Informatics and Molecular Modeling-based Approaches in Drug Repurposing M. Barrett and D. Frail (Eds.) Chap. 7, 163-194, Wiley and Sons.
- S.J. Ho Sui, R. Lo, R. Fernandes, M.DG.Caulfield, J. Lerman, L. Xie, P.E. Bourne, D.L.Baillie and F.S.L.Brinkman 2012 "Raloxifene attenuates Pseudomonas aeruginosa pyocyanin production and virulence". Int. J. of Antimicrobial Agents 40(3):246-251 [PDF].
- L. Xie, L. Xie, S. L. Kinnings, and P.E. Bourne 2012 "Novel Computational Approaches to Polypharmacology as a Means to Define Responses to Individual Drugs". Annu. Rev. Pharmacol. Toxicol. 52: 361-379 [PDF].