Investigating meta-approaches for reconstructing gene networks in a mammalian cellular context.

ABSTRACT: The output of state-of-the-art reverse-engineering methods for biological networks is often based on the fitting of a mathematical model to the data. Typically, different datasets do not give single consistent network predictions but rather an ensemble of inconsistent networks inferred under the same reverse-engineering method that are only consistent with the specific experimentally measured data. Here, we focus on an alternative approach for combining the information contained within such an ensemble of inconsistent gene networks called meta-analysis, to make more accurate predictions and to estimate the reliability of these predictions. We review two existing meta-analysis approaches; the Fisher transformation combined coefficient test (FTCCT) and Fisher's inverse combined probability t

SUBMITTER: Nazri A 

PROVIDER: S-EPMC3253778 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature