Co-expression networks: graph properties and topological comparisons
Open accessAbstract
Motivation: Microarray-based gene expression data have been generated widely to study different biological processes and systems. Gene co-expression networks are often used to extract information about groups of genes that are ‘functionally’ related or co-regulated. However, the structural properties of such co-expression networks have not been rigorously studied and fully compared with known biological networks. In this article, we aim at investigating the structural properties of co-expression networks inferred for the species Saccharomyces Cerevisiae and comparing them with the topological properties of the known, well-established transcriptional network, MIPS physical network and protein–protein interaction (PPI) network of yeast. Results: These topological comparisons indicate that co-expression networks are not distinctly related with either the PPI or the MIPS physical interaction networks, showing important structural differences between them. When focusing on a more literal comparison, vertex by vertex and edge by edge, the conclusion is the same: the fact that two genes exhibit a high gene expression correlation degree does not seem to obviously correlate with the existence of a physical binding between the proteins produced by these genes or the existence of a MIPS physical interaction between the genes. The comparison of the yeast regulatory network with inferred yeast co-expression networks would suggest, however, that they could somehow be related. Conclusions: We conclude that the gene expression-based co-expression networks reflect more on the gene regulatory networks but less on the PPI or MIPS physical interaction networks. Contact: hongzhe@mail.med.upenn.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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Literature broadly has reported common co-regulation of genes in protein complexes at both transcription and translational levels.
“This is a unique finding since literature broadly has reported common co-regulation of genes in protein complexes at both transcription and translational levels96–102.”
From EXOSC3 G191 Variants Trigger System-Wide Recalibration of RNA Processing Machinery (2026) · cites this paper as [101]
The Conclusions and Discussion report strong gene-expression correlations for protein pairs in permanent complexes and note that a few large complexes appear in both protein-interaction and co-expression networks. The paper does not report co-regulation at the translational level, and it describes the overall relationship between expression and protein interactions as weak. Page numbers are unavailable in our copy. (LLM, conf=0.85)
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Bhardwaj, N., & Lu, H. (2005) · Bioinformatics · doi:10.1093/bioinformatics/bti398 · Cited by 186 · see citing works
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Mistry, M., Gillis, J., & Pavlidis, P. (2013) · BMC Neuroscience · doi:10.1186/1471-2202-14-105 · Cited by 59 · see citing works
Sudhakar, P., Verstockt, B., Cremer, J., Verstockt, S., Sabino, J., Ferrante, M., & Vermeire, S. (2021) · Inflammatory Bowel Diseases · doi:10.1093/ibd/izaa281 · Cited by 49 · see citing works
EXOSC3 G191 Variants Trigger System-Wide Recalibration of RNA Processing Machinery
Wijeratne, H. R. S., Runnebohm, A. M., Barron, M. P., Hampton, A. J., Li, R., Peck Justice, S. A., Lenceski, S. H., Rooney, J. D., Smith-Kinnaman, W. R., Chang, G. S., et al. (2026) · doi:10.64898/2026.01.26.701775 · Cited by 1 · see citing works
- Authors
- Xulvi-Brunet, R., & Li, H.
- Affiliations
- Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
- University of Pennsylvania (US)
- Corresponding author
- Li, Hongzhe
- ORCID
- Li, Hongzhe
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2009-11-12
- Volume
- 26
- Issue
- 2
- Pages
- 205-214
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- PMC
- PMC2804297
- OpenAlex
- W2118636185
- Cited by
- 77
- References
- 1
- Citations by year
- 2026: 2 · 2024: 2 · 2023: 15 · 2022: 2 · 2021: 4 · 2020: 7 · 2019: 7 · 2018: 3 · 2017: 2 · 2016: 6 · 2015: 3 · 2014: 4 · 2013: 6 · 2012: 5
- FWCI
- 1.88
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Bioinformatics (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health
- National Cancer Institute (R01CA127334)
- National Institute of Environmental Health Sciences (R01ES009911)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Keywords
- gene co-expression network, network topology, Saccharomyces cerevisiae, protein-protein interaction network, transcriptional regulatory networks, gene regulatory networks, network structural properties, microarray gene expression, network comparison
- MeSH terms
- Saccharomyces cerevisiae, Computational Biology, Oligonucleotide Array Sequence Analysis, Protein Interaction Mapping, Databases, Genetic, Gene Regulatory Networks
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