Skip to main content
Article thumbnail
Location of Repository

G: Weighted Consensus Clustering for Identifying Functional Modules in Protein-Protein Interaction Networks

By Yi Zhang, Erliang Zeng, Tao Li and Giri Narasimhan


In this article we present a new approach- weighted consensus clustering to identify the clusters in Protein-protein interaction (PPI) networks where each cluster corresponds to a group of functionally similar proteins. In weighed consensus clustering, different input clustering results weigh differently, i.e., a weight for each input clustering is introduced and the weights are automatically determined by an optimization process. We evaluate our proposed method with standard measures such as modularity, normalized mutual information (NMI) and the Gene Ontology (GO) consortium database and compare the performance of our approach with other consensus clustering methods. Experimental results demonstrate the effectiveness of our proposed approach. 1

Year: 2013
OAI identifier: oai:CiteSeerX.psu:
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • (external link)
  • (external link)
  • Suggested articles

    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.