Differentiating party and date hubs in protein interaction networks using semantic similarity measures

Authors:
Edward Casey Kenley;Lyles Kirk;Young-Rae Cho
Affiliations:
Baylor University, Waco, Texas;Baylor University, Waco, Texas;Baylor University, Waco, Texas
Venue:
Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine
Year:
2011

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Abstract

Protein-protein interactions are fundamental to the biological processes within a cell. In the scale-free, small-world network typically modeled by protein interaction networks, hubs play a key role in maintaining the network structure. From the biological perspective, hubs are expected to be functionally essential proteins, participating in critical interactions of biological processes. Hubs can be classified into two different categories, party hubs (intra-module hubs) and date hubs (intermodule hubs), which vary in the timing and place of their associations with their interacting partners. This paper introduces a novel measure for identifying and differentiating party and date hubs in a protein interaction network. Our approach is based on the semantic similarity measure integrated with Gene Ontology data. Combined with the centrality measures of degree, betweenness, and closeness, we demonstrate that this measure detects potential party hubs and date hubs that match the confirmed party and date hubs with high accuracy.