A topological measurement for weighted protein interaction network

High-throughput methods for detecting protein-protein interactions (PPl) have given researchers an initial global picture of protein interactions on a genomic scale. The usefulness of this understanding is, however, typically compromised by noisy data. The effective way of integrating and using thes...

Full description

Saved in:
Bibliographic Details
Main Authors: Pei, P., Zhang, A.
Format: Conference Proceeding
Language:English
Subjects:
Algorithms
Bioinformatics
Biological processes
Biological system modeling
Computer science
Computer Simulation
data integration
Fungi
Genomics
Mass spectroscopy
Models, Biological
Network topology
Protein engineering
Protein Interaction Mapping - methods
protein interaction network
Protein-protein interaction
Proteome - metabolism
Signal Transduction - physiology
small world network
topological measurement
Weight measurement
weighted graph model
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:High-throughput methods for detecting protein-protein interactions (PPl) have given researchers an initial global picture of protein interactions on a genomic scale. The usefulness of this understanding is, however, typically compromised by noisy data. The effective way of integrating and using these non-congruent data sets has received little attention to date. This paper proposes a model to integrate different data sets. We construct this model using our prior knowledge of data set reliability. Based on this model, we propose a topological measurement to select reliable interactions and to quantify the similarity between two proteins' interaction profiles. Our measurement exploits the small-world network topological properties of protein interaction network. Meanwhile, we discovered some additional properties of the network. We show that our measurement can be used to find reliable interactions with improved performance and to find protein pairs with higher function homogeneity.
ISSN:1551-7497
DOI:10.1109/CSB.2005.8