# Understanding the temperature response of biological systems: Part II -- Network-level mechanisms and emergent dynamics

Source: [Understanding the temperature response of biological systems: Part II -- Network-level mechanisms and emergent dynamics](<https://www.sota2.com/research/paper/695f39f053fdd5c361743ef2>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-03-12T05:00:04.726Z

Authors: Simen Jacobs, Julian B. Voits, Nikita Frolov, Ulrich S. Schwarz, Lendert Gelens

Published: 2026-01-06T08:42:51.000Z

## Abstract

Building on the phenomenological and microscopic models reviewed in Part I, this second part focuses on network-level mechanisms that generate emergent temperature response curves. We review deterministic models in which temperature modulates the kinetics of coupled biochemical reactions, as well as stochastic frameworks, such as Markov chains, that capture more complex multi-step processes. These approaches show how Arrhenius-like temperature dependence at the level of individual reactions is transformed into non-Arrhenius scaling, thermal limits, and temperature compensation at the system level. Together, network-level models provide a mechanistic bridge between empirical temperature response curves and the molecular organization of biological systems, giving us predictive insights into robustness, perturbations, and evolutionary constraints.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2601.03307>)

[PDF](<https://arxiv.org/pdf/2601.03307.pdf>)