Hypergraphs and centrality measures identifying key features in gene expression data-Reference-Cited by-同舟云学术

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Hypergraphs and centrality measures identifying key features in gene expression data

Published:2023-12 Issue: Volume:366 Page:109089
ISSN:0025-5564
Container-title:Mathematical Biosciences
language:en
Short-container-title:Mathematical Biosciences

Author:

Barton Samuel^ORCID,Broad Zoe,Ortiz-Barrientos Daniel,Donovan Diane,Lefevre James

Funder

Australian Research Council Centre of Excellence for Plant Success in Nature and Agriculture

Publisher

Elsevier BV

Subject

Applied Mathematics,General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,Modeling and Simulation,General Medicine,Statistics and Probability

Reference50 articles.

1. A gene-coexpression network for global discovery of conserved genetic modules;Stuart;Science,2003

2. WGCNA: an r package for weighted correlation network analysis;Langfelder;BMC Bioinformatics,2008

3. Higher-Order Networks;Bianconi,2021

4. Hypergraph models of biological networks to identify genes critical to pathogenic viral response;Feng;BMC Bioinformatics,2021

5. Hypergraphs and cellular networks;Klamt;PLoS Comput. Biol.,2009

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