Title
Discovering functional interaction patterns in protein-protein interaction networks
Abstract
BACKGROUND: In recent years, a considerable amount of research effort has been directed to the analysis of biological networks with the availability of genome-scale networks of genes and/or proteins of an increasing number of organisms. A protein-protein interaction (PPI) network is a particular biological network which represents physical interactions between pairs of proteins of an organism. Major research on PPI networks has focused on understanding the topological organization of PPI networks, evolution of PPI networks and identification of conserved subnetworks across different species, discovery of modules of interaction, use of PPI networks for functional annotation of uncharacterized proteins, and improvement of the accuracy of currently available networks. RESULTS: In this article, we map known functional annotations of proteins onto a PPI network in order to identify frequently occurring interaction patterns in the functional space. We propose a new frequent pattern identification technique, PPISpan, adapted specifically for PPI networks from a well-known frequent subgraph identification method, gSpan. Existing module discovery techniques either look for specific clique-like highly interacting protein clusters or linear paths of interaction. However, our goal is different; instead of single clusters or pathways, we look for recurring functional interaction patterns in arbitrary topologies. We have applied PPISpan on PPI networks of Saccharomyces cerevisiae and identified a number of frequently occurring functional interaction patterns. CONCLUSION: With the help of PPISpan, recurring functional interaction patterns in an organism's PPI network can be identified. Such an analysis offers a new perspective on the modular organization of PPI networks. The complete list of identified functional interaction patterns is available at http://bioserver.ceng.metu.edu.tr/PPISpan/.
Year
DOI
Venue
2008
10.1186/1471-2105-9-276
BMC Bioinformatics
Keywords
Field
DocType
Gene Ontology, Frequent Pattern, Interaction Pattern, Depth First Search, Frequent Itemset Mining
Protein protein interaction network,Biology,Gene ontology,Biological network,Proteome,Bioinformatics,DNA microarray,Organism
Journal
Volume
Issue
ISSN
9
1
1471-2105
Citations 
PageRank 
References 
30
0.45
33
Authors
2
Name
Order
Citations
PageRank
Mehmet E. Turanalp1300.45
Tolga Can226816.39