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Multi-functional Protein Clustering in PPI Networks

  • Conference paper
Bioinformatics Research and Development (BIRD 2008)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 13))

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Abstract

Protein-Protein Interaction (PPI) networks contain valuable information for the isolation of groups of proteins that participate in the same biological function. Many proteins play different roles in the cell by taking part in several processes, but isolating the different processes in which a protein is involved is often a difficult task. In this paper we present a method based on a greedy local search technique to detect functional modules in PPI graphs. The approach is conceived as a generalization of the algorithm PINCoC to generate overlapping clusters of the interaction graph in input. Due to this peculiarity, multi-facets proteins are allowed to belong to different groups corresponding to different biological processes. A comparison of the results obtained by our method with those of other well known clustering algorithms shows the capability of our approach to detect different and meaningful functional modules.

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Authors and Affiliations

Authors

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Mourad Elloumi Josef Küng Michal Linial Robert F. Murphy Kristan Schneider Cristian Toma

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© 2008 Springer-Verlag Berlin Heidelberg

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Pizzuti, C., Rombo, S.E. (2008). Multi-functional Protein Clustering in PPI Networks . In: Elloumi, M., Küng, J., Linial, M., Murphy, R.F., Schneider, K., Toma, C. (eds) Bioinformatics Research and Development. BIRD 2008. Communications in Computer and Information Science, vol 13. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70600-7_24

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  • DOI: https://doi.org/10.1007/978-3-540-70600-7_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-70598-7

  • Online ISBN: 978-3-540-70600-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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