The generic temperature response of large biochemical networks

[2403.17202] The generic temperature response of large biochemical networks Skip to main content Search Submit Donate Log in Physics > Biological Physics arXiv:2403.17202 (physics) [Submitted on 25 Mar 2024 ( v1 ), last revised 8 Oct 2025 (this version, v3)] Title: The generic temperature response of large biochemical networks Authors: Julian B. Voits , Ulrich S. Schwarz (Heidelberg University) View PDF HTML (experimental) Abstract: Biological systems are remarkably susceptible to relatively small temperature changes. The most obvious example is fever, when a modest rise in body temperature of only few Kelvin has strong effects on our immune system and how it fights pathogens. Another very important example is climate change, when even smaller temperature changes lead to dramatic shifts in ecosystems. Although it is generally accepted that the main effect of an increase in temperature is the acceleration of biochemical reactions according to the Arrhenius equation, it is not clear how it affects large biochemical networks with complicated architectures. For developmental systems like fly and frog, it has been shown that the system response to temperature deviates in a characteristic manner from the linear Arrhenius plot of single reactions, but a rigorous explanation has not been given yet. Here we use a graph-theoretical interpretation of the mean first-passage times of a biochemical master equation to give a statistical description. We find that in the limit of large system size and if the network has a bias towards a target state, then the Arrhenius plot is generically quadratic, in excellent agreement with numerical simulations for large networks as well as with experimental data for developmental times in fly and frog. We also discuss under which conditions this generic response can be violated, for example for linear chains, which have only one spanning tree. Comments: 25 pages, 24 figures Subjects: Biological Physics (physics.bio-ph) ; Statistical Mechanics (cond-mat.stat-mech); Molecular Networks (q-bio.MN) Cite as: arXiv:2403.17202 [physics.bio-ph] (or arXiv:2403.17202v3 [physics.bio-ph] for this version) https://doi.org/10.48550/arXiv.2403.17202 Focus to learn more arXiv-issued DOI via DataCite Journal reference: PRX Life 3, 043011 (2025) Related DOI : https://doi.org/10.1103/nyr3-5my3 Focus to learn more DOI(s) linking to related resources Submission history From: Ulrich S. Schwarz [ view email ] [v1] Mon, 25 Mar 2024 21:27:38 UTC (1,237 KB) [v2] Tue, 5 Aug 2025 13:39:43 UTC (3,049 KB) [v3] Wed, 8 Oct 2025 12:20:29 UTC (3,126 KB) Full-text links: Access Paper: View PDF HTML (experimental) TeX Source view license Current browse context: physics.bio-ph < prev | next > new | recent | 2024-03 Change to browse by: cond-mat cond-mat.stat-mech physics q-bio q-bio.MN References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from

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