A model comparison study of the flowering time regulatory network in Arabidopsis.

ABSTRACT:

Background

Several dynamic models of a gene regulatory network of the light-induced floral transition process in Arabidopsis have been developed to capture the behavior of gene transcription and infer predictions based on experimental observations. It has been proven that the models can make accurate and novel predictions, which generate testable hypotheses.Two major issues were addressed in this study. First, construction of dynamic models for gene regulatory networks requires the use of mathematic modeling that comprises equations of a large number of parameters. Second, the binding mechanism of the transcription factor with DNA is another factor that requires detailed modeling. The first issue was tackled by adopting an optimization algorithm, and the second was addressed by com

SUBMITTER: Wang CC 

PROVIDER: S-EPMC3938817 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature