Pseudo-Random Fluctuations, Stochastic Cooperativity and Burstiness in Dynamically Unstable High-Dimensional Biochemical Networks
Simon Rosenfeld

TL;DR
This paper explores how high-dimensional nonlinear biochemical networks naturally exhibit bursty, stochastic behavior due to rare events and redundancy, leading to pseudo-random fluctuations without external noise or bistability.
Contribution
It introduces the concept of stochastic cooperativity and links burstiness to heavy-tailed distributions, showing how deterministic systems can display intrinsic stochasticity.
Findings
Burstiness arises from rare confluence events in gene expression.
High-dimensionality and nonlinearity lead to heavy-tailed stochastic processes.
Systems can exhibit stationary pseudo-random fluctuations inherently.
Abstract
The goal of this paper is to outline a scenario of emerging stochasticity in high-dimensional highly nonlinear systems, such as genetic regulatory networks (GRN). We focus attention on the fact that in such systems confluence of all the factors necessary for gene expression is a comparatively rare event, and only massive redundancy makes such events sufficiently frequent. An immediate consequence of this rareness is burstiness in mRNA and protein copy numbers, a well known experimentally observed effect. We introduce the concept of stochastic cooperativity and show that this phenomenon is a natural consequence of high dimensionality coupled with highly nonlinearity of a dynamical system. In mathematical terms, burstiness is associated with heavy-tailed probability distributions of stochastic processes describing the dynamics of the system. The sequence of stochastic cooperativity events…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsGene Regulatory Network Analysis · Evolution and Genetic Dynamics · thermodynamics and calorimetric analyses
