ArticleCell2009
Defining network topologies that can achieve biochemical adaptation.
Article in Cell, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 448 papers.
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Who cites it
448 citing papers in PubMed.
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- Signal Amplification in the HPT Axis-Evidence for Its Existence, Location, Significance, and Molecular Mechanisms.Acta physiologica (Oxford, England) · 2026Review
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- Incoherent feedforward loop dominates the robustness and tunability of necroptosis biphasic, emergent, and coexistent dynamics.Fundamental research · 2026Article
- Distinct impact of PI(4)P flux on PI(4,5)PProceedings of the National Academy of Sciences of the United States of America · 2026Article
- The adaptation property in non-equilibrium chemical systems.Journal of mathematical biology · 2026Article
- Carbon-phosphorus exchange rate constrains density-speed trade-off in arbuscular mycorrhizal fungal growth.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- A complex network perspective on brain disease.Biological reviews of the Cambridge Philosophical Society · 2026Review
- Translating Nature's Design Rules: How Catalysis and Life Science Guide Molecular Catassembly.JACS Au · 2026Review
- Article
388 more citing papers are in PubMed but not listed here.
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5 authors.
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Abstract
Many signaling systems show adaptation-the ability to reset themselves after responding to a stimulus. We computationally searched all possible three-node enzyme network topologies to identify those that could perform adaptation. Only two major core topologies emerge as robust solutions: a negative feedback loop with a buffering node and an incoherent feedforward loop with a proportioner node. Minimal circuits containing these topologies are, within proper regions of parameter space, sufficient to achieve adaptation. More complex circuits that robustly perform adaptation all contain at least one of these topologies at their core. This analysis yields a design table highlighting a finite set of adaptive circuits. Despite the diversity of possible biochemical networks, it may be common to find that only a finite set of core topologies can execute a particular function. These design rules provide a framework for functionally classifying complex natural networks and a manual for engineering networks. For a video summary of this article, see the PaperFlick file with the Supplemental Data available online.
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