Generating confidence intervals on biological networks

Background: In the analysis of networks we frequently require the statistical significance of some network statistic, such as measures of similarity for the properties of interacting nodes. The structure of the network may introduce dependencies among the nodes and it will in general be necessary to account for these dependencies in the statistical analysis. To this end we require some form of Null model of the network: generally rewired replicates of the network are generated which preserve only the degree (number of interactions) of each node. We show that this can fail to capture important features of network structure, and may result in unrealistic significance levels, when potentially confounding additional information is available. Methods: We present a new network resampling Null model which takes into account the degree sequence as well as available biological annotations. Using gene ontology information as an illustration we show how this information can be accounted for in t...

• Type: Journal
• Year: 2007
• Where: BMCBI
• Authors: Thomas Thorne, Michael P. H. Stumpf
• Keywords: BMCBI 2007, Null Model, Protein Interaction Network, Statistical Significance