Article

DynaMorph: self-supervised learning of morphodynamic states of live cells

2020-07-21

Abstract excerpt

The cell’s shape and motion represent fundamental aspects of the cell identity, and can be highly predictive of the function and pathology. However, automated analysis of the morphodynamic states remains challenging for most cell types, especially primary human cells where genetic labeling may not be feasible. To enable automated and quantitative analysis of morphodynamic states, we developed DynaMorph – a computa...

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Literature Corpus work: 6482a5f1-7365-5588-ace5-66ae8e76d37b
DOI: 10.1101/2020.07.20.213074

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