ArticleThe Journal of chemical physics2016
A framework for discrete stochastic simulation on 3D moving boundary domains.
Article in The Journal of chemical physics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
8 citing papers in PubMed.
- Three-dimensional stochastic simulation of chemoattractant-mediated excitability in cells.PLoS computational biology · 2021Article
- Cell polarisation in a bulk-surface model can be driven by both classic and non-classic Turing instability.NPJ systems biology and applications · 2021Article
- Coordinating cell polarization and morphogenesis through mechanical feedback.PLoS computational biology · 2021Article
- NERDSS: A Nonequilibrium Simulator for Multibody Self-Assembly at the Cellular Scale.Biophysical journal · 2020Article
- An implicit lipid model for efficient reaction-diffusion simulations of protein binding to surfaces of arbitrary topology.The Journal of chemical physics · 2019Article
- A hybrid smoothed dissipative particle dynamics (SDPD) spatial stochastic simulation algorithm (sSSA) for advection-diffusion-reaction problems.Journal of computational physics · 2019Article
- The effect of cell geometry on polarization in budding yeast.PLoS computational biology · 2018Article
- Reaction rates for reaction-diffusion kinetics on unstructured meshes.The Journal of chemical physics · 2017Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
We have developed a method for modeling spatial stochastic biochemical reactions in complex, three-dimensional, and time-dependent domains using the reaction-diffusion master equation formalism. In particular, we look to address the fully coupled problems that arise in systems biology where the shape and mechanical properties of a cell are determined by the state of the biochemistry and vice versa. To validate our method and characterize the error involved, we compare our results for a carefully constructed test problem to those of a microscale implementation. We demonstrate the effectiveness of our method by simulating a model of polarization and shmoo formation during the mating of yeast. The method is generally applicable to problems in systems biology where biochemistry and mechanics are coupled, and spatial stochastic effects are critical.
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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.