title: A topological measurement for weighted protein interaction network.
abstract: High-throughput methods for detecting protein-protein interactions (PPI) 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.
authors.affiliation: Department of Computer Science and Engineering, State University of New York at Buffalo, Buffalo, NY 14260, USA. ppei@cse.buffalo.edu
authors.forename: Pengjun
authors.initials: P
authors.lastname: Pei
authors.forename: Aidong
authors.initials: A
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D008954:Models, Biological; D025941:Protein Interaction Mapping / Q000379:methods*; D020543:Proteome / Q000378:metabolism*; D015398:Signal Transduction / Q000502:physiology*
chemical_list: D020543:Proteome