Abstract
Mitosis is essential for the growth, development and homeostasis of eukaryotes. Kinetochores are protein machines that control mitotic progression by forming dynamic force-generating attachments to spindle microtubules. Here, we will use super-resolution microscopy to image large numbers of kinetochores at distinct mitotic stages at a resolution of tens of nm. A cutting-edge deep learning approach will be used to fit the data, where the training process of the network is used to optimise a model with no prior constraints being applied. This model will be integrated from data from live-cell experiments to create the first nanoscale model of kinetochore dynamics.
References
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