Specificity and Stability in Topology of Protein Networks
Open accessAbstract
Molecular networks guide the biochemistry of a living cell on multiple levels: Its metabolic and signaling pathways are shaped by the network of interacting proteins, whose production, in turn, is controlled by the genetic regulatory network. To address topological properties of these two networks, we quantified correlations between connectivities of interacting nodes and compared them to a null model of a network, in which all links were randomly rewired. We found that for both interaction and regulatory networks, links between highly connected proteins are systematically suppressed, whereas those between a highly connected and low-connected pairs of proteins are favored. This effect decreases the likelihood of cross talk between different functional modules of the cell and increases the overall robustness of a network by localizing effects of deleterious perturbations.
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The CFG model is mathematically equivalent to the Maslov-Sneppen edge-swapping null model.
“With these conditions, this CFG model is mathematically equivalent to the Maslov–Sneppen edge-swapping null model66–68.”
From Network statistics of the whole-brain connectome of Drosophila (2024) · cites this paper as [66]
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- Authors
- Maslov, S., & Sneppen, K.
- Affiliations
- Brookhaven National Laboratory (US)
- Norwegian University of Science and Technology (NO)
- Corresponding author
- Maslov, Sergei
- Venue
- Science
- Published
- 2002-05-03
- Volume
- 296
- Issue
- 5569
- Pages
- 910-913
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2156737316
- Cited by
- 3,051
- References
- 3
- Citations by year
- 2026: 87 · 2025: 92 · 2024: 78 · 2023: 103 · 2022: 158 · 2021: 132 · 2020: 153 · 2019: 130 · 2018: 173 · 2017: 159 · 2016: 150 · 2015: 154 · 2014: 153 · 2013: 164 · 2012: 145
- FWCI
- 29.09
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Keywords
- protein-protein interaction network, gene regulatory networks, network topology, node connectivity, null models, random rewiring, crosstalk, network robustness, functional modules, metabolic pathways, signaling pathways
- MeSH terms
- Cell Nucleus, Nuclear Proteins, Probability, Protein Binding, Saccharomyces cerevisiae, Transcription, Genetic, Gene Expression Regulation, Fungal, Genome, Fungal, Computational Biology, Two-Hybrid System Techniques, Saccharomyces cerevisiae Proteins
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