Abstract
Modeling protein interactions as complex networks allow applying graph theory to help understanding their topology, to validate previous evidences and to uncover new biological associations. Topological properties have been recognized by their contribution for the understanding of the structures, functional relationships and evolution of complex networks, helping in a better comprehension of the diseases mechanisms and in the identification of drug targets. The human interactome, i.e. the network formed by all protein-protein interactions, is a complex and yet unknown system.
In this paper we present the results of a study about the topological properties of the oral protein network. We evaluate several confidence scores and prediction methods, in order to compare these networks with random organizations with the same size.
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Barbosa, F.C., Arrais, J.P., Oliveira, J.L. (2013). Quantitative Characterization of Protein Networks of the Oral Cavity. In: Mohamad, M., Nanni, L., Rocha, M., Fdez-Riverola, F. (eds) 7th International Conference on Practical Applications of Computational Biology & Bioinformatics. Advances in Intelligent Systems and Computing, vol 222. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00578-2_9
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DOI: https://doi.org/10.1007/978-3-319-00578-2_9
Publisher Name: Springer, Heidelberg
Print ISBN: 978-3-319-00577-5
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