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An Observation Data Driven Simulation and Analysis Framework for Early Stage &i&C. elegans&/i& Embryogenesis

机译:用于早期C的观测数据驱动的仿真和分析框架。线虫/ i胚胎发生

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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.
机译:尖端实时显微镜和图像分析的最新发展为系统研究单个细胞的动力学以及基于模拟的假设检验提供了独特的机会。在总结了与秀丽隐杆线虫胚胎发生相关的观察和建模工作中的数据生成和分析之后,我们开发了一种系统的方法来对单个细胞的基本行为进行建模。接下来,我们介绍在基于代理的建模框架中使用3D延时图像对细胞命运,分裂和运动进行建模的想法。然后,我们总结了初步结果并讨论了细胞命运,分裂和运动建模方面的工作。最后,我们讨论了秀丽隐杆线虫胚胎建模的正在进行的工作和未来的方向,包括推断出的细胞命运发展态势,拟定细胞分裂的准平衡模型以及用于细胞运动的多智能体,深度强化学习。

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