2022
DOI: 10.3389/fphy.2022.881885
|View full text |Cite
|
Sign up to set email alerts
|

Mass-Conservation Increases Robustness in Stochastic Reaction-Diffusion Models of Cell Crawling

Abstract: The process of polarization determines the head and tail of single cells. A mechanism of this kind frequently precedes the subsequent cell locomotion and it determines the direction of motion. The process of polarization has frequently been described as a reaction-diffusion mechanism combined with a source of stochastic perturbations. We selected a particular model of amoeboid cell crawling for the motion of Dictyostelium discoideum and studied the interplay between pattern formation and locomotion. Next, we i… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2024
2024
2024
2024

Publication Types

Select...
1
1

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(1 citation statement)
references
References 55 publications
0
1
0
Order By: Relevance
“…At its essence, SPDEs elegantly merge the unpredictability of stochastic processes with the foundational principles of partial differential equations (PDEs), providing a robust framework for the mathematical modeling of physical phenomena with randomness, alongside the spatial and temporal dynamics inherent in them. The versatility and depth of SPDEs have led to their application in a diverse range of fields, from the intricate patterns of physics to the innovative designs of engineering [1][2][3][4][5], the fluctuating dynamics of financial markets [6][7][8][9][10], and the complex processes within biological sciences [11][12][13][14][15][16]. This cross-disciplinary enthusiasm highlights the crucial importance of SPDEs in deepening our understanding of the world, connecting theoretical exploration with pragmatic resolutions to complex problems.…”
Section: Introductionmentioning
confidence: 99%
“…At its essence, SPDEs elegantly merge the unpredictability of stochastic processes with the foundational principles of partial differential equations (PDEs), providing a robust framework for the mathematical modeling of physical phenomena with randomness, alongside the spatial and temporal dynamics inherent in them. The versatility and depth of SPDEs have led to their application in a diverse range of fields, from the intricate patterns of physics to the innovative designs of engineering [1][2][3][4][5], the fluctuating dynamics of financial markets [6][7][8][9][10], and the complex processes within biological sciences [11][12][13][14][15][16]. This cross-disciplinary enthusiasm highlights the crucial importance of SPDEs in deepening our understanding of the world, connecting theoretical exploration with pragmatic resolutions to complex problems.…”
Section: Introductionmentioning
confidence: 99%