What is it about?
This work focuses on how cell migration is affected and regulated by mechanisms that are intrinsic to cells. We propose a novel mathematical description for the stabilization of sub-cellular structures and show that switches in migration modes can be explained by a correlation module e.g. "memory of migration". We have used Fractional Brownian Motion (fBm) and an Agent Based Model (ABM) to test different parameter combinations and analyze the effect that external cues (taxis) have in combination with the intrinsic mechanisms.
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Photo by National Cancer Institute on Unsplash
Why is it important?
Most mathematical descriptions of biological systems utilize standard stochastic components (mainly "white noise") to describe the variability observed across different iterations of the same process. We propose that this stochasticity is actually a "correlated process", which can be more appropriately modeled by using fractional Brownian motion. By analyzing how fBm is at interplay with other cell interactions, we observe variability in modes of migration that better resembles experimental observations at the single cell level.
Perspectives
We hope this article helps bridge biophysics and cell biology with computational methods through an engineering prospective, to help integrate an accurate representation of cell migration and its transitions, key to characterize physiologically relevant processes such as cancer progression. We hope this is the start of a framework aiming to characterize but also predict the behavior of cancer cells.
Ignacio Montenegro-Rojas
Pontificia Universidad Catolica de Chile
Read the Original
This page is a summary of: Modeling cell migratory persistence through temporal correlations and angular noise, PLOS One, May 2026, PLOS,
DOI: 10.1371/journal.pone.0349382.
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