Abstract
In this work we propose a novel hybrid technique for overlapping community detection in biological networks able to exploit both the available quantitative and the semantic information, that we call Semantically Enriched Fuzzy C-Means Spectral Modularity (SE-FSM) community detection method. We applied SE-FSM in analyzing Protein-protein interactions (PPIs) networks of HIV-1 infection and Leukemia in Homo sapiens. SE-FSM found significant overlapping biological communities. In particular, it found a strong relationship between HIV-1 and Leukemia as their communities share several significant pathways, and biological functions.
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Mahmoud, H., Masulli, F., Rovetta, S., Russo, G. (2015). Detecting Overlapping Protein Communities in Disease Networks. In: DI Serio, C., Liò, P., Nonis, A., Tagliaferri, R. (eds) Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2014. Lecture Notes in Computer Science(), vol 8623. Springer, Cham. https://doi.org/10.1007/978-3-319-24462-4_10
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DOI: https://doi.org/10.1007/978-3-319-24462-4_10
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