A Fast Agglomerate Algorithm for Mining Functional Modules in Protein Interaction Networks

As advanced in the technologies of predicting protein-protein interactions, huge data sets portrayed as networks have been generated. Identification of functional modules from such networks is crucial for understanding principles of cellular organization and functions. In this paper, we presented a new fast agglomerate algorithm of identifying functional modules based on the edge clustering coefficients, named FAG-EC. We applied algorithm FAG-EC to the core protein interaction network of budding yeast collected from DIP database. Many significant functional modules were detected. Algorithm FAG-EC had a high precision of more than 59% and had a recall of more than 27%. The f-measure was more than 37%. Most importantly, algorithm FAG-EC is extremely fast, which can be used in large protein interaction networks.