Learning the rules of collective cell migration using deep attention networks.

ABSTRACT: Collective, coordinated cellular motions underpin key processes in all multicellular organisms, yet it has been difficult to simultaneously express the 'rules' behind these motions in clear, interpretable forms that effectively capture high-dimensional cell-cell interaction dynamics in a manner that is intuitive to the researcher. Here we apply deep attention networks to analyze several canonical living tissues systems and present the underlying collective migration rules for each tissue type using only cell migration trajectory data. We use these networks to learn the behaviors of key tissue types with distinct collective behaviors-epithelial, endothelial, and metastatic breast cancer cells-and show how the results complement traditional biophysical approaches. In particular, we present a

SUBMITTER: LaChance J 

PROVIDER: S-EPMC9106212 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature