Estimating cellular redundancy in networks of genetic expression.
Cellular redundancy
Data analysis
Genetic expression
Hypergraphs
Spectral theory
Journal
Mathematical biosciences
ISSN: 1879-3134
Titre abrégé: Math Biosci
Pays: United States
ID NLM: 0103146
Informations de publication
Date de publication:
11 2021
11 2021
Historique:
received:
08
06
2021
revised:
22
07
2021
accepted:
06
09
2021
pubmed:
25
9
2021
medline:
25
9
2021
entrez:
24
9
2021
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 34560090
pii: S0025-5564(21)00128-0
doi: 10.1016/j.mbs.2021.108713
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
108713Informations de copyright
Copyright © 2021 Elsevier Inc. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.