Profiling Dynamic Patterns of Single-Cell Motility.

ABSTRACT: Cell motility plays an essential role in many biological processes as cells move and interact within their local microenvironments. Current methods for quantifying cell motility typically involve tracking individual cells over time, but the results are often presented as averaged values across cell populations. While informative, these ensemble approaches have limitations in assessing cellular heterogeneity and identifying generalizable patterns of single-cell behaviors, at baseline and in response to perturbations. In this study, CaMI is introduced, a computational framework designed to leverage the single-cell nature of motility data. CaMI identifies and classifies distinct spatio-temporal behaviors of individual cells, enabling robust classification of single-cell motility patterns in a

SUBMITTER: Maity D 

PROVIDER: S-EPMC11481225 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature