Optimizing static thermodynamic models of transcriptional regulation.

ABSTRACT:

Motivation

Modeling transcriptional regulation using thermo-dynamic modeling approaches has become increasingly relevant as a way to gain a detailed understanding of transcriptional regulation. Thermodynamic models are able to model the interactions between transcription factors (TFs) and DNA that lead to a specific transcriptional output of the target gene. Such models can be 'trained' by fitting their free parameters to data on the transcription rate of a gene and the concentrations of its regulating factors. However, the parameter fitting process is computationally very expensive and this limits the number of alternative types of model that can be explored.

Results

In this study, we evaluate the 'optimization landscape' of a class of static, quantitative models of regulat

SUBMITTER: Bauer DC 

PROVIDER: S-EPMC2732318 | biostudies-literature | 2009 Jul

REPOSITORIES: biostudies-literature