Semantic integration to identify overlapping functional modules in protein interaction networks.
BACKGROUND
The systematic analysis of protein-protein interactions can enable a better understanding of cellular organization, processes and functions. Functional modules can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of functional module detection algorithms.


RESULTS
We have developed novel metrics, called semantic similarity and semantic interactivity, which use Gene Ontology (GO) annotations to measure the reliability of protein-protein interactions. The protein interaction networks can be converted into a weighted graph representation by assigning the reliability values to each interaction as a weight. We presented a flow-based modularization algorithm to efficiently identify overlapping modules in the weighted interaction networks. The experimental results show that the semantic similarity and semantic interactivity of interacting pairs were positively correlated with functional co-occurrence. The effectiveness of the algorithm for identifying modules was evaluated using functional categories from the MIPS database. We demonstrated that our algorithm had higher accuracy compared to other competing approaches.


CONCLUSIONS
The integration of protein interaction networks with GO annotation data and the capability of detecting overlapping modules substantially improve the accuracy of module identification.
Cho
Young-Rae
YR
Department of Computer Science and Engineering, State University of New York, Buffalo, NY, USA. ycho8@cse.buffalo.edu
Hwang
Woochang
W
Ramanathan
Murali
M
Zhang
Aidong
A
D000465:Algorithms; D003198:Computer Simulation; D030562:Databases, Protein; D016247:Information Storage and Retrieval / Q000379:methods; D008954:Models, Biological; D009323:Natural Language Processing; D025941:Protein Interaction Mapping / Q000379:methods*; D020543:Proteome / Q000378:metabolism*; D012660:Semantics; D015398:Signal Transduction / Q000502:physiology*; D018511:Systems Integration
D020543:Proteome