Professional Education

  • Bachelor of Engineering, Tianjin University (2005)
  • Doctor of Philosophy, Duke University (2012)

Stanford Advisors


Journal Articles

  • Causal structure of oscillations in gene regulatory networks: Boolean analysis of ordinary differential equation attractors. Chaos Sun, M., Cheng, X., Socolar, J. E. 2013; 23 (2): 025104-?


    A common approach to the modeling of gene regulatory networks is to represent activating or repressing interactions using ordinary differential equations for target gene concentrations that include Hill function dependences on regulator gene concentrations. An alternative formulation represents the same interactions using Boolean logic with time delays associated with each network link. We consider the attractors that emerge from the two types of models in the case of a simple but nontrivial network: a figure-8 network with one positive and one negative feedback loop. We show that the different modeling approaches give rise to the same qualitative set of attractors with the exception of a possible fixed point in the ordinary differential equation model in which concentrations sit at intermediate values. The properties of the attractors are most easily understood from the Boolean perspective, suggesting that time-delay Boolean modeling is a useful tool for understanding the logic of regulatory networks.

    View details for DOI 10.1063/1.4807733

    View details for PubMedID 23822502

  • Autonomous Boolean modelling of developmental gene regulatory networks JOURNAL OF THE ROYAL SOCIETY INTERFACE Cheng, X., Sun, M., Socolar, J. E. 2013; 10 (78)


    During early embryonic development, a network of regulatory interactions among genes dynamically determines a pattern of differentiated tissues. We show that important timing information associated with the interactions can be faithfully represented in autonomous Boolean models in which binary variables representing expression levels are updated in continuous time, and that such models can provide a direct insight into features that are difficult to extract from ordinary differential equation (ODE) models. As an application, we model the experimentally well-studied network controlling fly body segmentation. The Boolean model successfully generates the patterns formed in normal and genetically perturbed fly embryos, permits the derivation of constraints on the time delay parameters, clarifies the logic associated with different ODE parameter sets and provides a platform for studying connectivity and robustness in parameter space. By elucidating the role of regulatory time delays in pattern formation, the results suggest new types of experimental measurements in early embryonic development.

    View details for DOI 10.1098/rsif.2012.0574

    View details for Web of Science ID 000311939400010

    View details for PubMedID 23034351

  • Characteristics of three-phase internal loop airlift bioreactors with complete gas recirculation for non-Newtonian fluids BIOPROCESS AND BIOSYSTEMS ENGINEERING Wen, J. P., Jia, X. Q., Cheng, X. R., Yang, P. 2005; 27 (3): 193-205


    Hydrodynamic and gas-liquid mass transfer characteristics, such as liquid velocity, gas holdup, solid holdup and gas-liquid volumetric mass transfer coefficient, in the riser and downcomer of the gas-liquid-solid three-phase internal loop airlift bioreactors with complete gas recirculation for non-Newtonian fluids, were investigated. A mathematical model for the description of flow behavior and gas-liquid mass transfer of these bioreactors was developed. The predicted results of this model agreed well with the experimental data.

    View details for DOI 10.1007/s00449-005-0401-9

    View details for Web of Science ID 000229641100006

    View details for PubMedID 15765215

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