Inference of quantitative models of bacterial promoters from time-series reporter gene data.

ABSTRACT: The inference of regulatory interactions and quantitative models of gene regulation from time-series transcriptomics data has been extensively studied and applied to a range of problems in drug discovery, cancer research, and biotechnology. The application of existing methods is commonly based on implicit assumptions on the biological processes under study. First, the measurements of mRNA abundance obtained in transcriptomics experiments are taken to be representative of protein concentrations. Second, the observed changes in gene expression are assumed to be solely due to transcription factors and other specific regulators, while changes in the activity of the gene expression machinery and other global physiological effects are neglected. While convenient in practice, these assumptions ar

SUBMITTER: Stefan D 

PROVIDER: S-EPMC4295839 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature