Filling kinetic gaps: dynamic modeling of metabolism where detailed kinetic information is lacking.

ABSTRACT:

Background

Integrative analysis between dynamical modeling of metabolic networks and data obtained from high throughput technology represents a worthy effort toward a holistic understanding of the link among phenotype and dynamical response. Even though the theoretical foundation for modeling metabolic network has been extensively treated elsewhere, the lack of kinetic information has limited the analysis in most of the cases. To overcome this constraint, we present and illustrate a new statistical approach that has two purposes: integrate high throughput data and survey the general dynamical mechanisms emerging for a slightly perturbed metabolic network.

Methodology/principal findings

This paper presents a statistic framework capable to study how and how fast the metabolite

SUBMITTER: Resendis-Antonio O 

PROVIDER: S-EPMC2654918 | biostudies-literature | 2009

REPOSITORIES: biostudies-literature