Assemble Predicted Clusters For better Proteins Cluster Detection
Detecting protein complexes from protein-protein interaction (PPI) network is becoming a difficult challenge in computational biology. There is ample evidence that many disease mechanisms involve protein complexes, and being able to predict these complexes is important to the characterization of the relevant disease for diagnostic and treatment purposes. Popular methods such as MCL, MCODE, CMC, ClusterOne and PEWCC demonstrated great ability to detect protein complexes. PCM is developed to assemble the protein lists detected by the above mentioned methods and produce a better protein complex list. A new Complex graph is simulated where each complex detected from the mentioned methods and two nodes are connected by an edge if similarity measure of two clusters (nodes) > by a defined overlap threshold. Connectivity analysis is then run on the cluster graph generated in previous step. For each connected component, if number of clusters in a given component >= min. number of clusters given by user, all the clusters are merged to form a single cluster (union of graphs), otherwise the component is discarded. Each component which is merged as a single cluster now represents a protein complex. All the complexes are available in results panel with other interactive features to extract as separate sub-network (or) to export the complexes to a text file.


Works with Cytoscape 3.2


Version 1.0

Released 27 Feb 2017

Works with Cytoscape 3.2

Download Stats Click here