Jerarca: Efficient Analysis of Complex Networks Using Hierarchical Clustering
There are many types of data, both biological and non-biological, which can be represented as undirected graphs. Examples in biology are networks based on protein-protein interaction data, those based on shared protein domains, genetic interaction networks or co-expression networks. Developing heuristic strategies to extract useful information from them is an active field of research (reviewed in). A typical problem is how to generate partitions of a network in order to establish clusters, groups of tightly connected units. There are two basic general strategies to perform such a task. One option is to search for densely connected modules, for instance using a local evaluation function that measures when adding or eliminating units leads to a significant decrease of the average density of connections within a group (see e.g. refs).