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Estimating cellular redundancy in networks of genetic expression

Research output: Contribution to Journal › Article › Academic › peer-review

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.
Original languageEnglish
Article number108713
Pages (from-to)1-7
Number of pages7
JournalMathematical Biosciences
Volume341
Early online date22 Sept 2021
DOIs
Publication statusPublished - Nov 2021
Externally publishedYes

Funding

RM was supported by The Alan Turing Institute under the EPSRC, UK grant EP/N510129/1 .

FundersFunder number
Alan Turing Institute
Engineering and Physical Sciences Research CouncilEP/N510129/1

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