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 ident...

• Type: Journal
• Year: 2007
• Where: BMCBI
• Authors: Young-Rae Cho, Woochang Hwang, Murali Ramanathan, Aidong Zhang
• Keywords: BMCBI 2007, Interaction Networks, Protein Interaction, Protein-protein Interactions