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Home / News

Why noise may be the key to understanding cell group patterns

Noise is everywhere in nature, and deterministic models often fail to fully account for its influence. (image: Unsplash)
May 12, 2026

All of biology is transient. Over time, a population of identical cells can change so that some subgroups exhibit different behaviors — everything from varying sizes to the expression of certain proteins, or regulation of processes like metabolism. Cell biologists have long assumed that these population-scale behaviors are determined by individual-level mechanisms, and that observations of these subgroups can reveal what happens at the single-cell level.

Mathematical biologist and SFI Postdoctoral Fellow James Holehouse says it’s time to challenge that assumption. In a recent paper in Proceedings of the Royal Society B, Holehouse describes real-world counterexamples in which population-level cellular patterns don’t correspond to individual behaviors. “This is a complete breakdown of those previous assumptions,” he says. “What we see on the population level is completely not reflected, if you look at the trajectories of individuals in that population.”

If researchers want a better understanding of how collective behaviors emerge, he says, they should consider the interplay between transience and randomness more seriously. Holehouse has long studied the role of noise, or randomness, in cellular processes like metabolism and how cells produce the right number and balance of proteins. And what he’s found is that the behavior of the collective can’t be entirely explained by tracing the deterministic changes in individual cells, or in the steady states of populations of randomly varying cells.

Holehouse looked at specific cases where conventional models of cell biology—those based on the idea that individuals should determine group patterns—would predict only a single possible mode.  But in the new paper, he shows how transient, time-dependent effects, a fundamental property of biological systems, can lead to two distinct modes, or subpopulations of cells, in a population of identical cells that only appear equipped to produce a single mode. Two distinct modes can emerge if a model takes stochasticity, or random noise, into account.

In the past, says Holehouse, researchers relied primarily on deterministic models and treated noise as a kind of disturbance to those solutions. But noise is everywhere in nature, and deterministic models often fail to fully account for its influence. That omission, he says, could inhibit the ability of models to fully predict how cellular systems use regulatory systems that become more or less important over time. A cell subject to extreme heat, for example, activates survival pathways as a transient — or temporary — response.

“Understanding the novel behaviors that come about through stochastic processes interacting in a time-dependent setting,” he says, “tells us something very, very important about regulation in transient settings. It gives rise to an entirely new space of novel biological behaviors.”

Holehouse is continuing to develop his approach, identifying which processes produce the phenomenon of transient bimodality described in the new paper. “These types of phenomena have some very non-intuitive ways of realizing themselves,” he says. “It’s important that we understand the many origins of cellular differentiation, and that biological mechanisms get attributed to the correct qualitative explanations.”
 

Read the paper “Do distinct subpopulations signify modes of behaviour in a noisy single cell?” in Proceedings of the Royal Society B (May 6, 2026). DOI: 10.1098/rspb.2026.0134





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