Building Predictive Models of Genetic Circuits Using the Principle of Maximum Caliber.

ABSTRACT: Learning the underlying details of a gene network is a major challenge in cellular and synthetic biology. We address this challenge by building a chemical kinetic model that utilizes information encoded in the stochastic protein expression trajectories typically measured in experiments. The applicability of the proposed method is demonstrated in an auto-activating genetic circuit, a common motif in natural and synthetic gene networks. Our approach is based on the principle of maximum caliber (MaxCal)-a dynamical analog of the principle of maximum entropy-and builds a minimal model using only three constraints: 1) protein synthesis, 2) protein degradation, and 3) positive feedback. The MaxCal-generated model (described with four parameters) was benchmarked against synthetic data generated u

SUBMITTER: Firman T 

PROVIDER: S-EPMC5685677 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature