ReviewBMC biophysics2014
Simulation tools for particle-based reaction-diffusion dynamics in continuous space.
Review in BMC biophysics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- Continuum and discrete modeling of binding-site distribution-mediated reactions on lipid surfaces.Biophysical journal · 2026Article
- Evolution of competitive systems in nature.Scientific reports · 2025Article
- Engineering a Novel Probiotic Toolkit inACS synthetic biology · 2024Article
- Interplay between stochastic enzyme activity and microtubule stability drives detyrosination enrichment on microtubule subsets.Current biology : CB · 2023Article
- Implications of different membrane compartmentalization models in particle-basedRoyal Society open science · 2023Article
- Towards modelling emergence in plant systems.Quantitative plant biology · 2023Article
- Quantifying the roles of space and stochasticity in computer simulations for cell biology and cellular biochemistry.Molecular biology of the cell · 2021Article
- pSpatiocyte: a high-performance simulator for intracellular reaction-diffusion systems.BMC bioinformatics · 2020Article
- Potential based, spatial simulation of dynamically nested particles.BMC bioinformatics · 2019Article
- An implicit lipid model for efficient reaction-diffusion simulations of protein binding to surfaces of arbitrary topology.The Journal of chemical physics · 2019Article
- ReaDDy 2: Fast and flexible software framework for interacting-particle reaction dynamics.PLoS computational biology · 2019Article
- A spatio-temporal model reveals self-limiting FcRoyal Society open science · 2018Article
- Fluctuating Finite Element Analysis (FFEA): A continuum mechanics software tool for mesoscale simulation of biomolecules.PLoS computational biology · 2018Article
- Particle-based simulations of polarity establishment reveal stochastic promotion of Turing pattern formation.PLoS computational biology · 2018Article
- Challenges in Reproducibility, Replicability, and Comparability of Computational Models and Tools for Neuronal and Glial Networks, Cells, and Subcellular Structures.Frontiers in neuroinformatics · 2018Article
- Molecular simulations of cellular processes.Biophysical reviews · 2017Review
- Multiscale Modeling of Diffusion in a Crowded Environment.Bulletin of mathematical biology · 2017Article
- Protein-peptide association kinetics beyond the seconds timescale from atomistic simulations.Nature communications · 2017Article
- Lipid-mediated PX-BAR domain recruitment couples local membrane constriction to endocytic vesicle fission.Nature communications · 2017Article
- Excluded volume effects in on- and off-lattice reaction-diffusion models.IET systems biology · 2017Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Particle-based reaction-diffusion algorithms facilitate the modeling of the diffusional motion of individual molecules and the reactions between them in cellular environments. A physically realistic model, depending on the system at hand and the questions asked, would require different levels of modeling detail such as particle diffusion, geometrical confinement, particle volume exclusion or particle-particle interaction potentials. Higher levels of detail usually correspond to increased number of parameters and higher computational cost. Certain systems however, require these investments to be modeled adequately. Here we present a review on the current field of particle-based reaction-diffusion software packages operating on continuous space. Four nested levels of modeling detail are identified that capture incrementing amount of detail. Their applicability to different biological questions is discussed, arching from straight diffusion simulations to sophisticated and expensive models that bridge towards coarse grained molecular dynamics.
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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.