ArticlePloS one2012
A linear framework for time-scale separation in nonlinear biochemical systems.
Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 62 papers.
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Who cites it
62 citing papers in PubMed.
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- Decoupling between activation time and steady-state level in input-output responses.PLoS computational biology · 2026Article
- Braess' Paradox in Enzyme Kinetics: Asymmetry from Population Balance without Direct Cooperativity.Journal of chemical theory and computation · 2026Article
- Widespread low-affinity motifs enhance chromatin accessibility and regulatory potential in mESCs.bioRxiv : the preprint server for biology · 2025Article
- Algebraic formulas for first-passage times of Markov processes in the linear framework.Bulletin of mathematical biology · 2025Article
- Emergence of activation or repression in transcriptional control under a fixed molecular context.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Decoupling between activation time and steady-state level in input-output responses.bioRxiv : the preprint server for biology · 2025Article
- Limits on the computational expressivity of non-equilibrium biophysical processes.Nature communications · 2025Article
- A mathematical model clarifies the ABC Score formula used in enhancer-gene prediction.bioRxiv : the preprint server for biology · 2024Article
- Deciphering regulatory architectures of bacterial promoters from synthetic expression patterns.PLoS computational biology · 2024Article
- Flexibility and sensitivity in gene regulation out of equilibrium.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Seeing with an extra sense.Current biology : CB · 2024Article
- Kinetic Diagram Analysis: A Python Library for Calculating Steady-State Observables of Biochemical Systems Analytically.Journal of chemical theory and computation · 2024Article
- Kinetic Diagram Analysis: A Python Library for Calculating Steady-State Observables of Biochemical Systems Analytically.bioRxiv : the preprint server for biology · 2024Article
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- Deciphering regulatory architectures from synthetic single-cell expression patterns.bioRxiv : the preprint server for biology · 2024Article
- The Hill function is the universal Hopfield barrier for sharpness of input-output responses.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
2 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
- Erratum issued
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cellular physiology is implemented by formidably complex biochemical systems with highly nonlinear dynamics, presenting a challenge for both experiment and theory. Time-scale separation has been one of the few theoretical methods for distilling general principles from such complexity. It has provided essential insights in areas such as enzyme kinetics, allosteric enzymes, G-protein coupled receptors, ion channels, gene regulation and post-translational modification. In each case, internal molecular complexity has been eliminated, leading to rational algebraic expressions among the remaining components. This has yielded familiar formulas such as those of Michaelis-Menten in enzyme kinetics, Monod-Wyman-Changeux in allostery and Ackers-Johnson-Shea in gene regulation. Here we show that these calculations are all instances of a single graph-theoretic framework. Despite the biochemical nonlinearity to which it is applied, this framework is entirely linear, yet requires no approximation. We show that elimination of internal complexity is feasible when the relevant graph is strongly connected. The framework provides a new methodology with the potential to subdue combinatorial explosion at the molecular level.
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