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. © 2014 Springer International Publishing Switzerland.
CITATION STYLE
Mahmoud, H., Masulli, F., Rovetta, S., & Russo, G. (2014). Community detection in protein-protein interaction networks using spectral and graph approaches. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8452 LNBI, pp. 62–75). Springer Verlag. https://doi.org/10.1007/978-3-319-09042-9_5
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