Abstract

AbstractRapid 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

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