Estimation and discrimination of stochastic biochemical circuits from time-lapse microscopy data.

ABSTRACT: The ability of systems and synthetic biologists to observe the dynamics of cellular behavior is hampered by the limitations of the sensors, such as fluorescent proteins, available for use in time-lapse microscopy. In this paper, we propose a generalized solution to the problem of estimating the state of a stochastic chemical reaction network from limited sensor information generated by microscopy. We mathematically derive an observer structure for cells growing under time-lapse microscopy and incorporates the effects of cell division in order to estimate the dynamically-changing state of each cell in the colony. Furthermore, the observer can be used to discrimate between models by treating model indices as states whose values do not change with time. We derive necessary and sufficient cond

SUBMITTER: Thorsley D 

PROVIDER: S-EPMC3491022 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature