ArticleBiophysical journal2018
Steady-State Differential Dose Response in Biological Systems.
Article in Biophysical journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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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.
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Who cites it
9 citing papers in PubMed.
- A Human Glucoregulatory Model for the Rational Design and Evaluation of Diabetes Therapeutics.ACS pharmacology & translational science · 2026Article
- Decoupling between activation time and steady-state level in input-output responses.PLoS computational biology · 2026Article
- Algebraic formulas for first-passage times of Markov processes in the linear framework.Bulletin of mathematical biology · 2025Article
- Decoupling between activation time and steady-state level in input-output responses.bioRxiv : the preprint server for biology · 2025Article
- Re-evaluation of the risks to public health related to the presence of bisphenol A (BPA) in foodstuffs.EFSA journal. European Food Safety Authority · 2023Article
- The linear framework II: using graph theory to analyse the transient regime of Markov processes.Frontiers in cell and developmental biology · 2023Article
- The linear framework: using graph theory to reveal the algebra and thermodynamics of biomolecular systems.Interface focus · 2022Review
- Allosteric conformational ensembles have unlimited capacity for integrating information.eLife · 2021Article
- Efficient manipulation and generation of Kirchhoff polynomials for the analysis of non-equilibrium biochemical reaction networks.Journal of the Royal Society, Interface · 2020Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In pharmacology and systems biology, it is a fundamental problem to determine how biological systems change their dose-response behavior upon perturbations. In particular, it is unclear how topologies, reactions, and parameters (differentially) affect the dose response. Because parameters are often unknown, systematic approaches should directly relate network structure and function. Here, we outline a procedure to compare general non-monotone dose-response curves and subsequently develop a comprehensive theory for differential dose responses of biochemical networks captured by non-equilibrium steady-state linear framework models. Although these models are amenable to analytical derivations of non-equilibrium steady states in principle, their size frequently increases (super) exponentially with model size. We extract general principles of differential responses based on a model's graph structure and thereby alleviate the combinatorial explosion. This allows us, for example, to determine reactions that affect differential responses, to identify classes of networks with equivalent differential, and to reject hypothetical models reliably without needing to know parameter values. We exemplify such applications for models of insulin signaling.
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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.