Moving in the mesoscale: Understanding the mechanics of cytoskeletal molecular motors by combining mesoscale simulations with imaging
Moving in the mesoscale: Understanding the mechanics of cytoskeletal molecular motors by combining mesoscale simulations with imaging
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DOI：
10.1002/wcms.1570
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发表时间：
2021-08-21
影响因子：
11.4
通讯作者：
Harris, Sarah A.
中科院分区：
文献类型：
--
作者：
Gravett, Molly S. C.;Cocking, Ryan C.;Harris, Sarah A.
实验生物物理技术的快速发展产生了大量关于细胞骨架及其马达的机械操作的信息。然而，这些工具中的每一个通常只提供高度复杂的难题的有限部分。有必要开发新的计算工具，将这些数据整合到一个中央模型中。在这里，我们讨论了实验的进展，以及计算工具，并提出如何开发这些可以成功地结合联合收割机新兴的结构和动态实验数据的细胞骨架电机。我们考虑生物细胞内的单个马达和马达阵列的例子。本文分类下：结构和机制>分子结构数据科学>计算机算法和编程数据科学>可视化
Rapid advances in experimental biophysical techniques are generating a wealth of information about the mechanical operation of the cellular cytoskeleton and its motors. However, each of these tools typically provides only a limited piece of a highly complex puzzle. There is a need to develop new computational tools that can integrate these data together into a central model. Here we discuss the experimental advances alongside the computational tools, and propose how these could be developed to successfully combine the emerging structural and dynamic experimental data on cytoskeletal motors. We consider examples of both single motors and arrays of motors within a biological cell. This article is categorized under: Structure and Mechanism > Molecular Structures Data Science > Computer Algorithms and Programming Data Science > Visualization