Computational Methods for Detecting Functional Modules from Gene Regulatory Network

In systems biology, a group of genes constitutes a functional module (group of tightly interconnected nodes) involved in common elementary biological functions. Identifying such modules is helpful in system level understanding of biological and cellular processes. As a result predicting such functional modules based on expression patterns of genes is an active research issue in the area of computational biology. A number of techniques have been proposed so far to find functional modules that are densely connected, involving in common biological functions. These methods are broadly categorised into non-network based gene expression clustering techniques and network based methods that extract modules from gene interaction networks. In this work, we try to review some of the promising network module finding techniques and compare their effectiveness in extracting biologically significant modules. We use gene ontology to validate the quality of modules extracted by each candidate method and compare their relative effectiveness.