Identifying interactions in the time and frequency domains in local and global networks - A Granger Causality Approach.

ABSTRACT:

Background

Reverse-engineering approaches such as Bayesian network inference, ordinary differential equations (ODEs) and information theory are widely applied to deriving causal relationships among different elements such as genes, proteins, metabolites, neurons, brain areas and so on, based upon multi-dimensional spatial and temporal data. There are several well-established reverse-engineering approaches to explore causal relationships in a dynamic network, such as ordinary differential equations (ODE), Bayesian networks, information theory and Granger Causality.

Results

Here we focused on Granger causality both in the time and frequency domain and in local and global networks, and applied our approach to experimental data (genes and proteins). For a small gene network, Gra

SUBMITTER: Zou C 

PROVIDER: S-EPMC2897832 | biostudies-literature | 2010 Jun

REPOSITORIES: biostudies-literature