ArticleProceedings of the National Academy of Sciences of the United States of America2022
Universal structural requirements for maximal robust perfect adaptation in biomolecular networks.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. 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 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- GenAI-Net: A generative AI framework for automated biomolecular network design.Science advances · 2026Article
- Toward single-cell control: noise-robust perfect adaptation in biomolecular systems.Nature communications · 2025Article
- The inherent fragility of collective proliferative control.iScience · 2025Article
- Cumulative dose responses for adapting biological systems.Journal of the Royal Society, Interface · 2025Article
- Topological criterion for robust perfect adaptation of reaction fluxes in biological networks.iScience · 2025Article
- Multi-Layer Autocatalytic Feedback Enables Integral Control Amidst Resource Competition and Across Scales.ACS synthetic biology · 2025Article
- A distributed integral control mechanism for regulation of cholesterol concentration in the human retina.Royal Society open science · 2024Article
- Anti-windup strategies for biomolecular control systems facilitated by model reduction theory for sequestration networks.Science advances · 2024Article
- Homeostasis in networks with multiple inputs.Journal of mathematical biology · 2024Article
- Competition and evolutionary selection among core regulatory motifs in gene expression control.Nature communications · 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
- Low-distortion information propagation with noise suppression in swarm networks.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Robust homeostasis of cellular cholesterol is a consequence of endogenous antithetic integral control.Frontiers in cell and developmental biology · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Adaptation is a running theme in biology. It allows a living system to survive and thrive in the face of unpredictable environments by maintaining key physiological variables at their desired levels through tight regulation. When one such variable is maintained at a certain value at the steady state despite perturbations to a single input, this property is called robust perfect adaptation (RPA). Here we address and solve the fundamental problem of maximal RPA (maxRPA), whereby, for a designated output variable, RPA is achieved with respect to perturbations in virtually all network parameters. In particular, we show that the maxRPA property imposes certain structural constraints on the network. We then prove that these constraints are fully characterized by simple linear algebraic stoichiometric conditions which differ between deterministic and stochastic descriptions of the dynamics. We use our results to derive a new internal model principle (IMP) for biomolecular maxRPA networks, akin to the celebrated IMP in control theory. We exemplify our results through several known biological examples of robustly adapting networks and construct examples of such networks with the aid of our linear algebraic characterization. Our results reveal the universal requirements for maxRPA in all biological systems, and establish a foundation for studying adaptation in general biomolecular networks, with important implications for both systems and synthetic biology.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.