Jianhua Xing, Ph.D.

  • Associate Professor
  • Department of Computational and Systems Biology

Education & Training

  • Ph.D. in Theoretical Chemistry from the University of California Berkeley, 2002
  • M.S. in Chemical Physics from University of Minnesota Twin Cities, 1998
  • B.S. in Physical Chemistry from Peking University, China, 1996

Research Interest Summary

Use quantitative systems biology approaches to study cell fate decision and transformation related to cancer metastasis and fibrosis.

Research Categories

Research Interests

We are interested in the following fundamental questions. How do thousands of molecules species orchestrate temporally and spatially to determine a cell phenotype? How can one regulate and direct cell phenotype? Specifically, the lab currently focuses on Epithelial-to-Mesenchymal Transition (EMT), characterized by loss of cell-cell adhesion and increased cell motility. EMT plays important roles in embryonic development, tissue regeneration, wound healing and pathological processes such as fibrosis in lung, liver, and kidney, and cancer metastasis. The lab studies the coupled gene expression and epigenetic dynamics of EMT. Guided by mathematical models, we perform quantitative measurements on the dynamics of involved molecular species, which then feed into models for further predictions to test.

Representative Publications

W. Wang, D. L. Douglas, J. Zhang, S. Kumari, M. S. Enuameh, Y. Dai, C. T. Wallace, S. C. Watkins, W. Shu, J. H. Xing, Live cell imaging and analysis reveal cell phenotypic transition dynamics inherently missing in snapshot data, Science Advances, 6:eaba9309 (2020).

J. Zhang, H. Chen, R. Li, G. Yao, F. Bai, Guang Yao, and J. H. Xing, Spatial clustering and common regulatory elements correlate with coordinated gene expression, PLOS Computational Biology, 15:e1006786 (2019).

W. Wang, D. A. Taft, Y.-J. Chen, J. Zhang, C. Wallace, M. Xu, S. C. Watkins, J. H. Xing, Learn to segment single cells with deep distance estimator and deep cell detector, Computers in Biology and Medicine, 108: 133-141 (2019).

X.J. Tian, H. Zhang, J. Sannerud and J. Xing. Achieving diverse and monoallelic olfactory receptor selection through dual-objective optimization design. PNAS, 113:2889 (2016).

X.J. Tian, H. Zhang, J. Zhang and J. Xing. mRNA-miRNA reciprocal regulation enabled bistable switch directs cell fate decision. FBES Letters, 590. 3443-3455 (2016).

J. H. Xing, J. Yu H. Zhang, and X-J Tian. Computational modeling to elucidate mechanisms of epigenetic memory, in Epigenetic Technological Applications (Elsevier, Editor: George Zheng), Elsevier (2015).

J. Zhang*, Xiao-Jun Tian*, Hang Zhang*, Elankumaran Subbiah, J. H. Xing, TGF-β–induced epithelial-to-mesenchymal transition proceeds through stepwise activation of multiple feedback loops, Science Signaling, 7:ra91 (2014).

P. Wang*, C. Song, H. Zhang*, Z. Wu*, X-J Tian*, J. H. Xing, Epigenetic state network approach for describing cell phenotypic transitions, Interface Focus, 4(3): 20130068 (2014).

H. Zhang*, X. Tian*, K. S. Kim, J. H. Xing, Statistical mechanics model for the dynamics of collective epigenetic histone modification, Physical Review Letters, 112: 068101 (2014).

X. Tian*, H. Zhang*, J. H. Xing, Coupled Reversible and Irreversible Bistable Switches Underlying TGF-beta-induced Epithelial to Mesenchymal Transition, Biophysical Journal, 105:1079-1089 (2013).

Full List of Publications