Mingyang Lu


  • PhD, Baylor College of Medicine, 2010


I received my B.S. degree in physics at Fudan University. Afterwards, I obtained my Ph.D. degree in Biochemistry and Molecular Biology at Baylor College of Medicine in the laboratory of Dr. Jianpeng Ma. During that time, I worked on computational methodology development for coarse-grained modeling of bimolecular structures and their applications to x-ray crystallographic refinement of flexible supramolecular complexes. I then worked as a postdoctoral fellow in the Center for Theoretical Biological Physics (CTBP) at Rice University with Dr. Jose Onuchic on computational systems biology. I currently works as an Assistant Professor at The Jackson Laboratory – Mammalian Genetics. My work includes the design of a new theoretical framework for microRNA-based genetic circuits and its application to the epithelial-mesenchymal transition (EMT) circuit, the construction of effective landscapes for multistable genetic switches in the presence of gene expression noises, the modeling of exosome-mediated cancer-immunity interplay, and the development of a network modeling method that captures the robustness, cell-to-cell variability and heterogeneity in gene expression dynamics. I received a CPRIT postdoctoral fellowship for two years in 2014. I am currently a member of American Physical Society (APS), the Biophysical Society (BPS) and the American Association for Cancer Research (AACR)

Research Interests

In the Lu lab at The Jackson Laboratory, we are passionate about the development and application of computational modeling methods to study the operating mechanisms of cancer genetic networks. Specifically, we use systems biology approaches to integrate computational modeling and data analysis to elucidate the relationship among robustness of network dynamics, stochasticity in gene expression and heterogeneity in cancer evolution. We are interested in the fundamental question of how cancer evolves through genetic and epigenetic alterations, especially how tumorigenesis is shaped by the architecture of gene regulatory networks. We aim to extend the scope of existing modeling scheme to large systems, and to take advantage of current available big data in the cancer biology community. Our studies will contribute to a systems-level understanding of cancer and will eventually lead to the design of personalized therapies for cancer patients.

Selected Publications

  • F. Bocci, Y. Suzuki, M. Lu, J. Onuchic. (2018) Role of metabolic spatiotemporal dynamics in regulating biofilm colony expansion. Proc. Natl. Acad. Sci. U.S.A. doi:10.1073/pnas.1706920115
  • F. Ye, D. Jia, M. Lu, H. H. Levine, M. W. Deem. (2018) Modularity of the metabolic gene network as a prognostic biomarker for hepatocellular carcinoma. Oncotarget. 9(19): 15015-26
  • D. Jia, M.K. Jolly, S.C. Tripathi, P.D. Hollander, B. Huang, M. Lu, M. Celiktas, E. Ramirez-Peña, E. Ben-Jacob, J.N. Onuchic, S.M. Hanash, S.A. Mani, H. Levine. (2017) Distinguishing mechanisms underlying EMT tristability. Cancer Converg. 1:2. https://doi.org/10.1186/s41236-017-0005-8
  • X. Tian, B. Huang, X. Zhang, M. Lu, F. Liu, J. Onuchic, W. Wang. (2017) Modeling the response of a tumor-suppressive network to mitogenic and oncogenic signals. Proc. Natl. Acad. Sci. U.S.A. 114(21):5337-42
  • B. Huang*, M. Lu*, D. Jia, E. Ben-Jacob, H. Levine, J. Onuchic. (2017) Interrogating the topological robustness of gene regulatory circuits by randomization. PLoS Comput Biol. 13(3):e1005456 (*equal contribution)
  • L. Yu*, M. Lu*#, D. Jia*, J. Ma, E. Ben-Jacob, H. Levine, B.A. Kaipparettu, J. Onuchic. (2017) Modeling the Genetic Regulation of Cancer Metabolism: Interplay Between Glycolysis and Oxidative Phosphorylation. Cancer Res. 77(7): 1564 (*equal contribution, #co-corresponding author)
  • M. Darash-Yahana *, Y. Pozniak*, M. Lu*, Y-S. Sohn, O. Karmi, S. Tamir, et al. Breast cancer tumorigenicity is dependent on high expression levels of NAF-1 and the lability of its Fe-S clusters. PNAS 113(39):10890–5. (*equal contribution)