Possible Rotation Projects:
- Mammalian cell culturing and live cell imaging to study cell fate transition.
- Analyze single cell RNA-seq data using our computational package dynamo
Training Technologies Used:
- Mathematical modeling
- qPCR
- Western blot
- Gene editing tools
- Single cell imaging and analysis
- 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
W. Wang, D. Poe, Y. Yang, T. Hyatt, J. H. Xing (2022), Epithelial-to-mesenchymal transition proceeds through directional destabilization of multidimensional attractor, eLife, 11:e74866. Note: selected as feature article.
Qiu, X., Y. Zhang, M.-R. J. D., C. Weng, S. Hosseinzadeh, D. Yang, L. Wang, R. Yuan, S. Xu, Y. Ma, J. Replogle, E. Lander, S. Darmanis, I. Bahar., V. Sankaran, J. H. Xing and J. S. Weissman (2022). "Mapping Transcriptomic Vector Fields of Single Cells." Cell 185(4): 690-711. (Qiu, Xing and Weissman as co-corresponding authors, and the Xing lab developed the theoretical and computational framework).
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).
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? The lab uses both computational and experimental approaches, and collaborate with other researchers locally, nationally, and internationally. Currently we focus on how cell cycle couples to cell fate decision and transition in the context of differentiation, drug responses, and reprogramming.
