Paper Info
Title
Topology-based scoring method for identification of responsive protein-protein interaction subnetwork
Abstract
In this article, we propose a novel topology-based scoring and searching approach to extract protein protein interaction (PPI) subnetworks responsive to conditions being investigated according gene expression profiles. Each subnetwork is scored using both the activity of individual vertices and the network topology, instead of summing up only the activity of vertices as done in previous works. Using simulated data we demonstrate the advantage of the proposed method when the subnetworks contain highly significant hub genes, or high number of co-activated gene pairs. When applied to the sample data galFiltered in Cytoscape, our algorithm identified several biologically meaningful subnetworks that contain genes missed by vertex based scoring approach. Lastly we apply the new method to a human prostate cancer dataset and show that it can efficiently identify disease-relevant protein interactions. The new method is implemented as a Cytoscape Plugin jActiveModuesTopo. It is publicly available and can be used on most types of gene expression data.
Year
DOI
Venue
2011
10.1109/BIBMW.2011.6112414
BIBM Workshops
Keywords
Field
DocType
sample data,disease-relevant protein interaction,responsive protein-protein interaction subnetwork,gene expression profile,biologically meaningful subnetworks,protein protein interaction,gene expression data,significant hub gene,new method,co-activated gene pair,topology-based scoring method,proteins,cancer,genetics,molecular biophysics,genomics,network topology
Topology,Gene,Protein–protein interaction,Vertex (geometry),Computer science,Network topology,Genomics,Algorithm theory,Molecular biophysics,Bioinformatics,Subnetwork
Conference
ISSN
ISBN
Citations 
2163-6966
978-1-4577-1612-6
0
PageRank 
References 
Authors
0.34
8
2
Name
Order
Citations
PageRank
Shouguo Gao1502.65
Xujing Wang2908.54