Traction force microscopy with optimized regularization and automated Bayesian parameter selection for comparing cells.

ABSTRACT: Adherent cells exert traction forces on to their environment which allows them to migrate, to maintain tissue integrity, and to form complex multicellular structures during developmental morphogenesis. Traction force microscopy (TFM) enables the measurement of traction forces on an elastic substrate and thereby provides quantitative information on cellular mechanics in a perturbation-free fashion. In TFM, traction is usually calculated via the solution of a linear system, which is complicated by undersampled input data, acquisition noise, and large condition numbers for some methods. Therefore, standard TFM algorithms either employ data filtering or regularization. However, these approaches require a manual selection of filter- or regularization parameters and consequently exhibit a substa

SUBMITTER: Huang Y 

PROVIDER: S-EPMC6345967 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature