Author(s)

Dali Wang^1,2, Zi Wang¹, Xiaopeng Zhao³, Yichi Xu⁴, Zhirong Bao⁴

¹Department of Electric Engineering and Computer Science, University of Tennessee, Knoxville, USA.
²Environmental Science Division, Oak Ridge National Laboratory, Oak Ridge, USA.
³Department of Mechanical, Aerospace and Biomedical Engineering, University of Tennessee, Knoxville, USA.
⁴Developmental Biology Program, Memorial Sloan Kettering Cancer Center, NYC, USA.

Recent developments in cutting-edge live microscopy and image analysis provide a unique opportunity to systematically investigate individual cell’s dynamics as well as simulation-based hypothesis testing. After a summary of data generation and analysis in the observation and modeling efforts related to C. elegans embryogenesis, we develop a systematic approach to model the basic behaviors of individual cells. Next, we present our ideas to model cell fate, division, and movement using 3D time-lapse images within an agent-based modeling framework. Then, we summarize preliminary result and discuss efforts in cell fate, division, and movement modeling. Finally, we discuss the ongoing efforts and future directions for C. elegans embryo modeling, including an inferred developmental landscape for cell fate, a quasi-equilibrium model for cell division, and multi-agent, deep reinforcement learning for cell movement.

C. elegans Embryogenesis, Agent-Based Modeling, Deep Reinforcement Learning, Observation-Driven Modeling Framework, 3D Live Images

Wang, D. , Wang, Z. , Zhao, X. , Xu, Y. and Bao, Z. (2018) An Observation Data Driven Simulation and Analysis Framework for Early Stage C. elegans Embryogenesis. Journal of Biomedical Science and Engineering, 11, 225-234. doi: 10.4236/jbise.2018.118018.