An inferential framework for biological network hypothesis tests.

ABSTRACT:

Background

Networks are ubiquitous in modern cell biology and physiology. A large literature exists for inferring/proposing biological pathways/networks using statistical or machine learning algorithms. Despite these advances a formal testing procedure for analyzing network-level observations is in need of further development. Comparing the behaviour of a pharmacologically altered pathway to its canonical form is an example of a salient one-sample comparison. Locating which pathways differentiate disease from no-disease phenotype may be recast as a two-sample network inference problem.

Results

We outline an inferential method for performing one- and two-sample hypothesis tests where the sampling unit is a network and the hypotheses are stated via network model(s). We propose

SUBMITTER: Yates PD 

PROVIDER: S-EPMC3621801 | biostudies-literature | 2013 Mar

REPOSITORIES: biostudies-literature