ArticleProceedings. Mathematical, physical, and engineering sciences2021
Ultrasensitivity and bistability in covalent-modification cycles with positive autoregulation.
Article in Proceedings. Mathematical, physical, and engineering sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Laser capture microdissection.Nature reviews. Methods primers · 2025Article
- A distributed integral control mechanism for regulation of cholesterol concentration in the human retina.Royal Society open science · 2024Article
- Bifunctional enzyme provides absolute concentration robustness in multisite covalent modification networks.Journal of mathematical biology · 2024Article
- Generalized Michaelis-Menten rate law with time-varying molecular concentrations.PLoS computational biology · 2023Article
- Only a topological method can identify all possible network structures capable of Robust Perfect Adaptation.PLoS computational biology · 2023Article
- Universal structures for adaptation in biochemical reaction networks.Nature communications · 2023Article
- Robust homeostasis of cellular cholesterol is a consequence of endogenous antithetic integral control.Frontiers in cell and developmental biology · 2023Article
- Protein-protein complexes can undermine ultrasensitivity-dependent biological adaptation.Journal of the Royal Society, Interface · 2023Article
- Emergence and Enhancement of Ultrasensitivity through Posttranslational Modulation of Protein Stability.Biomolecules · 2021Article
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2 authors.
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Abstract
Switch-like behaviours in biochemical networks are of fundamental significance in biological signal processing, and exist as two distinct types: ultra-sensitivity and bistability. Here we propose two new models of a reversible covalent-modification cycle with positive autoregulation (PAR), a motif structure that is thought to be capable of both ultrasensitivity and bistability in different parameter regimes. These new models appeal to a modelling framework that we call
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