Quantifying time-varying cellular secretions with local linear models.

ABSTRACT: Extracellular protein concentrations and gradients initiate a wide range of cellular responses, such as cell motility, growth, proliferation and death. Understanding inter-cellular communication requires spatio-temporal knowledge of these secreted factors and their causal relationship with cell phenotype. Techniques which can detect cellular secretions in real time are becoming more common but generalizable data analysis methodologies which can quantify concentration from these measurements are still lacking. Here we introduce a probabilistic approach in which local-linear models and the law of mass action are applied to obtain time-varying secreted concentrations from affinity-based biosensor data. We first highlight the general features of this approach using simulated data which contain

SUBMITTER: Byers JM 

PROVIDER: S-EPMC5506887 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature