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首页> 外文期刊>Critical Reviews in Biomedical Engineering >Multiscale Modeling of Cellular Epigenetic States: Stochasticity in Molecular Networks, Chromatin Folding in Cell Nuclei, and Tissue Pattern Formation of Cells
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Multiscale Modeling of Cellular Epigenetic States: Stochasticity in Molecular Networks, Chromatin Folding in Cell Nuclei, and Tissue Pattern Formation of Cells

机译：细胞表观遗传状态的多尺度建模：分子网络中的随机性，细胞核中的染色质折叠以及细胞的组织模式形成

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摘要

Genome sequences provide the overall genetic blueprint of cells, but cells possessing the same genome can exhibit diverse phenotypes. There is a multitude of mechanisms controlling cellular epigenetic states and that dictate the behavior of cells. Among these, networks of interacting molecules, often under stochastic control, depending on the specific wirings of molecular components and the physiological conditions, can have a different landscape of cellular states. In addition, chromosome folding in three-dimensional space provides another important control mechanism for selective activation and repression of gene expression. Fully differentiated cells with different properties grow, divide, and interact through mechanical forces and communicate through signal transduction, resulting in the formation of complex tissue patterns. Developing quantitative models to study these multi-scale phenomena and to identify opportunities for improving human health requires development of theoretical models, algorithms, and computational tools. Here we review recent progress made in these important directions.
机译：基因组序列提供了细胞的总体遗传蓝图，但是拥有相同基因组的细胞可以表现出不同的表型。控制细胞表观遗传状态的机制多种多样，它们决定了细胞的行为。其中，相互作用分子的网络通常在随机控制下，这取决于分子组分的特定连接方式和生理条件，可以具有不同的细胞状态。此外，染色体在三维空间中的折叠为选择性激活和抑制基因表达提供了另一个重要的控制机制。具有不同特性的完全分化的细胞通过机械力生长，分裂和相互作用，并通过信号转导进行通信，从而形成复杂的组织模式。开发定量模型以研究这些多尺度现象并确定改善人类健康的机会，需要开发理论模型，算法和计算工具。在这里，我们回顾了在这些重要方向上取得的最新进展。

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