A framework for scalable parameter estimation of gene circuit models using structural information.

ABSTRACT:

Motivation

Systematic and scalable parameter estimation is a key to construct complex gene regulatory models and to ultimately facilitate an integrative systems biology approach to quantitatively understand the molecular mechanisms underpinning gene regulation.

Results

Here, we report a novel framework for efficient and scalable parameter estimation that focuses specifically on modeling of gene circuits. Exploiting the structure commonly found in gene circuit models, this framework decomposes a system of coupled rate equations into individual ones and efficiently integrates them separately to reconstruct the mean time evolution of the gene products. The accuracy of the parameter estimates is refined by iteratively increasing the accuracy of numerical integration using the mo

SUBMITTER: Kuwahara H 

PROVIDER: S-EPMC3694671 | biostudies-literature | 2013 Jul

REPOSITORIES: biostudies-literature