ArticleSIAM journal on scientific computing : a publication of the Society for Industrial and Applied Mathematics2010
SIMULATING BIOCHEMICAL SIGNALING NETWORKS IN COMPLEX MOVING GEOMETRIES.
Article in SIAM journal on scientific computing : a publication of the Society for Industrial and Applied Mathematics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Tools for computational analysis of moving boundary problems in cellular mechanobiology.Wiley interdisciplinary reviews. Systems biology and medicine · 2020Review
- Simple Rho GTPase Dynamics Generate a Complex Regulatory Landscape Associated with Cell Shape.Biophysical journal · 2020Article
- Free boundary problem for cell protrusion formations: theoretical and numerical aspects.Journal of mathematical biology · 2017Article
- A computational method for the coupled solution of reaction-diffusion equations on evolving domains and manifolds: Application to a model of cell migration and chemotaxis.Journal of computational physics · 2016Article
- Signaling regulated endocytosis and exocytosis lead to mating pheromone concentration dependent morphologies in yeast.FEBS letters · 2012Article
- Deterministic versus stochastic cell polarisation through wave-pinning.Bulletin of mathematical biology · 2012Article
- How cells integrate complex stimuli: the effect of feedback from phosphoinositides and cell shape on cell polarization and motility.PLoS computational biology · 2012Article
- A comparison of computational models for eukaryotic cell shape and motility.PLoS computational biology · 2012Review
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Signaling networks regulate cellular responses to environmental stimuli through cascades of protein interactions. External signals can trigger cells to polarize and move in a specific direction. During migration, spatially localized activity of proteins is maintained. To investigate the effects of morphological changes on intracellular signaling, we developed a numerical scheme consisting of a cut cell finite volume spatial discretization coupled with level set methods to simulate the resulting advection-reaction-diffusion system. We then apply the method to several biochemical reaction networks in changing geometries. We found that a Turing instability can develop exclusively by cell deformations that maintain constant area. For a Turing system with a geometry-dependent single or double peak solution, simulations in a dynamically changing geometry suggest that a single peak solution is the only stable one, independent of the oscillation frequency. The method is also applied to a model of a signaling network in a migrating fibroblast.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.