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一种基于观察数据驱动的秀丽隐杆线虫早期胚胎发育模拟与分析框架。

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

作者信息

Wang Dali, Wang Zi, Zhao Xiaopeng, Xu Yichi, Bao Zhirong

机构信息

Department of Electric Engineering and Computer Science, University of Tennessee, Knoxville, 37996, USA.

Environmental Science Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA.

出版信息

J Biomed Sci Eng. 2018 Aug;11(8):225-234. doi: 10.4236/jbise.2018.118018. Epub 2018 Aug 28.

DOI:10.4236/jbise.2018.118018
PMID:35574576
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9097948/
Abstract

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.

摘要

前沿活体显微镜技术和图像分析的最新进展为系统研究单个细胞的动态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育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方法来模拟单个细胞的基本行为。接下来，我们提出了在基于智能体的建模框架内使用三维延时图像来模拟细胞命运、分裂和运动的想法。然后，我们总结了初步结果并讨论了在细胞命运、分裂和运动建模方面所做的工作。最后，我们讨论了秀丽隐杆线虫胚胎建模的当前工作和未来方向，包括细胞命运的推断发育景观、细胞分裂的准平衡模型以及细胞运动的多智能体深度强化学习。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb28/9097948/af76b9b1008e/nihms-1785511-f0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb28/9097948/8326623df634/nihms-1785511-f0001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb28/9097948/0adf040af27d/nihms-1785511-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb28/9097948/9f7de0ecada8/nihms-1785511-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb28/9097948/f030577a5622/nihms-1785511-f0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb28/9097948/af76b9b1008e/nihms-1785511-f0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb28/9097948/8326623df634/nihms-1785511-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb28/9097948/1a6bda166aab/nihms-1785511-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb28/9097948/5b8a576ca75e/nihms-1785511-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb28/9097948/0adf040af27d/nihms-1785511-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb28/9097948/9f7de0ecada8/nihms-1785511-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb28/9097948/f030577a5622/nihms-1785511-f0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb28/9097948/af76b9b1008e/nihms-1785511-f0007.jpg

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本文引用的文献

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Deep reinforcement learning of cell movement in the early stage of C.elegans embryogenesis.线虫胚胎发生早期细胞运动的深度强化学习。
Bioinformatics. 2018 Sep 15;34(18):3169-3177. doi: 10.1093/bioinformatics/bty323.
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An Observation-Driven Agent-Based Modeling and Analysis Framework for C. elegans Embryogenesis.一种基于观察驱动的秀丽隐杆线虫胚胎发育的基于主体的建模与分析框架。
PLoS One. 2016 Nov 16;11(11):e0166551. doi: 10.1371/journal.pone.0166551. eCollection 2016.
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