| Literature DB >> 34560090 |
Raffaella Mulas1, Michael J Casey2.
Abstract
Networks of genetic expression can be modeled by hypergraphs with the additional structure that real coefficients are given to each vertex-edge incidence. The spectra, i.e. the multiset of the eigenvalues, of such hypergraphs, are known to encode structural information of the data. We show how these spectra can be used, in particular, in order to give an estimation of cellular redundancy, a novel measure of gene expression heterogeneity, of the network. We analyze some simulated and real data sets of gene expression for illustrating the new method proposed here.Entities:
Keywords: Cellular redundancy; Data analysis; Genetic expression; Hypergraphs; Spectral theory
Year: 2021 PMID: 34560090 DOI: 10.1016/j.mbs.2021.108713
Source DB: PubMed Journal: Math Biosci ISSN: 0025-5564 Impact factor: 2.144