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 language | English |
|---|---|
| Article number | 108713 |
| Pages (from-to) | 1-7 |
| Number of pages | 7 |
| Journal | Mathematical Biosciences |
| Volume | 341 |
| Early online date | 22 Sept 2021 |
| DOIs | |
| Publication status | Published - Nov 2021 |
| Externally published | Yes |
Funding
RM was supported by The Alan Turing Institute under the EPSRC, UK grant EP/N510129/1 .
| Funders | Funder number |
|---|---|
| Alan Turing Institute | |
| Engineering and Physical Sciences Research Council | EP/N510129/1 |
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