The plugin provides a user-friendly implementation of ontology- and graph-based similarity assessment in biological networks. It can be used to analyze networks on a “semantic similarity” space to detect potentially novel associations, which may not be explicitly represented in the input network under analysis.
**New features in V2.0**
Prioritization of network clustering results. Given a set of network clusters (candidate modules) identified by a clustering algorithm, SimTrek selects and ranks potential biologically relevant clusters through: (1)The estimation of functional homogeneity scores for a set of given module based on the calculation of the average of functional similarity values over all interaction pairs in the cluster having annotations in the GO MySQL database; and (2) Assignment of a corrected statistical significance, Q, value to each Hom score based on a random permutation test
