Community Detection in Protein-Protein Interaction Networks Using Spectral and Graph Approaches

Inferring significant communities of interacting proteins is a main trend of current biological research, as this task can help in revealing the functionality and the relevance of specific macromolecular assemblies or even in discovering possible proteins affecting a specific biological process. Efficient algorithms able to find suitable communities inside proteins networks may support drug discovery and diseases treatment even in earlier stages. This paper employs spectral and graph clustering methodologies for discovering protein-protein interactions communities in the Saccharomyces cerevisiae protein-protein interaction network.