Go-or-grow models in biology: a monster on a leash

Go-or-grow approaches represent a specific class of mathematical models used to describe populations where individuals either migrate or reproduce, but not both simultaneously. These models have a wide range of applications in biology and medicine, chiefly among those the modeling of brain cancer spread. The analysis of go-or-grow models has inspired new mathematics, and it is the purpose of this review to highlight interesting and challenging mathematical properties of reaction-diffusion models of the go-or-grow type. We provide a detailed review of biological and medical applications before focusing on key results concerning solution existence and uniqueness, pattern formation, critical domain size problems, and traveling waves. We present new results related to the critical domain size and traveling wave problems, and we connect these findings to the existing literature. Moreover, we demonstrate the high level of instability inherent in go-or-grow models. We argue that there is currently no accurate numerical solver for these models, and emphasize that special care must be taken when dealing with the "monster on a leash".

Authors

Institutions

Publication Details

Journal
Journal of Mathematical Biology
Published
2025-10-16
DOI
https://doi.org/10.1007/s00285-025-02243-8
Citations
1
Primary Topic
Evolution and Genetic Dynamics
Type
article
Field-Weighted Citation Impact
1.82

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Go-or-grow models in biology: a monster on a leash

Thomas Hillen, Martina Conte, Tracy L. Stepien, Ryan Thiessen
1 citations
Journal of Mathematical Biology
Evolution and Genetic Dynamics
1.82
article

Go-or-grow models in biology: a monster on a leash

Thomas Hillen, Martina Conte, Tracy L. Stepien, Ryan Thiessen
article en
1 citations

Abstract

Go-or-grow approaches represent a specific class of mathematical models used to describe populations where individuals either migrate or reproduce, but not both simultaneously. These models have a wide range of applications in biology and medicine, chiefly among those the modeling of brain cancer spread. The analysis of go-or-grow models has inspired new mathematics, and it is the purpose of this review to highlight interesting and challenging mathematical properties of reaction-diffusion models of the go-or-grow type. We provide a detailed review of biological and medical applications before focusing on key results concerning solution existence and uniqueness, pattern formation, critical domain size problems, and traveling waves. We present new results related to the critical domain size and traveling wave problems, and we connect these findings to the existing literature. Moreover, we demonstrate the high level of instability inherent in go-or-grow models. We argue that there is currently no accurate numerical solver for these models, and emphasize that special care must be taken when dealing with the "monster on a leash".

Journal of Mathematical BiologyVol. 91(5)
University of Parma (IT), University of Alberta (CA), University of Florida (US)
Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 12%
Evolution and Genetic Dynamics
1.82
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.