Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/8535
Title: Quantifying randomness in protein-protein interaction networks of different species: A random matrix approach
Authors: Sarkar, Camellia
Dwivedi, Sanjiv Kumar
Jalan, Sarika
Keywords: Atmospheric spectra;Eigenvalues and eigenfunctions;Matrix algebra;Random processes;Random variables;Adjacency matrices;Long range correlations;Nearest-neighbor spacing distributions;Protein-protein interaction networks;Random matrix theory;Random-matrix approach;Spectral rigidity;Structural feature;Proteins
Issue Date: 2014
Publisher: Elsevier B.V.
Citation: Agrawal, A., Sarkar, C., Dwivedi, S. K., Dhasmana, N., & Jalan, S. (2014). Quantifying randomness in protein-protein interaction networks of different species: A random matrix approach. Physica A: Statistical Mechanics and its Applications, 404, 359-367. doi:10.1016/j.physa.2013.12.005
Abstract: We analyze protein-protein interaction networks for six different species under the framework of random matrix theory. Nearest neighbor spacing distribution of the eigenvalues of adjacency matrices of the largest connected part of these networks emulate universal Gaussian orthogonal statistics of random matrix theory. We demonstrate that spectral rigidity, which quantifies long range correlations in eigenvalues, for all protein-protein interaction networks follow random matrix prediction up to certain ranges indicating randomness in interactions. After this range, deviation from the universality evinces underlying structural features in network. © 2013 Elsevier B.V. All rights reserved.
URI: https://doi.org/10.1016/j.physa.2013.12.005
https://dspace.iiti.ac.in/handle/123456789/8535
ISSN: 0378-4371
Type of Material: Journal Article
Appears in Collections:Department of Physics

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