Inferring cell state by quantitative motility analysis reveals a dynamic state system and broken detailed balance.

ABSTRACT: Cell populations display heterogeneous and dynamic phenotypic states at multiple scales. Similar to molecular features commonly used to explore cell heterogeneity, cell behavior is a rich phenotypic space that may allow for identification of relevant cell states. Inference of cell state from cell behavior across a time course may enable the investigation of dynamics of transitions between heterogeneous cell states, a task difficult to perform with destructive molecular observations. Cell motility is one such easily observed cell behavior with known biomedical relevance. To investigate heterogenous cell states and their dynamics through the lens of cell behavior, we developed Heteromotility, a software tool to extract quantitative motility features from timelapse cell images. In mouse embry

SUBMITTER: Kimmel JC 

PROVIDER: S-EPMC5786322 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature