Stochastic reaction-diffusion simulation with MesoRD. Summary: MesoRD is a tool for stochastic simulation of chemical reactions and diffusion. In particular, it is an implementation of the next subvolume method, which is an exact method to simulate the Markov process corresponding to the reaction-diffusion master equation. Availability: MesoRD is free software, written in C++ and licensed under the GNU general public license (GPL). MesoRD runs on Linux, Mac OS X, NetBSD, Solaris and Windows XP. It can be downloaded from

References in zbMATH (referenced in 30 articles )

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  1. Bartosz J. Bartmanski; Ruth E. Baker: StoSpa2: A C++ software package for stochastic simulations of spatially extended systems (2020) not zbMATH
  2. Kang, Hye-Won; Erban, Radek: Multiscale stochastic reaction-diffusion algorithms combining Markov chain models with stochastic partial differential equations (2019)
  3. Lötstedt, Per: The linear noise approximation for spatially dependent biochemical networks (2019)
  4. Smith, Stephen; Grima, Ramon: Spatial stochastic intracellular kinetics: a review of modelling approaches (2019)
  5. Wei, Tengda; Lin, Ping; Wang, Yangfan; Wang, Linshan: Stability of stochastic impulsive reaction-diffusion neural networks with S-type distributed delays and its application to image encryption (2019)
  6. Bou-Rabee, Nawaf: SPECTRWM: spectral random walk method for the numerical solution of stochastic partial differential equations (2018)
  7. Burrage, Kevin; Burrage, Pamela; Leier, Andre; Marquez-Lago, Tatiana: A review of stochastic and delay simulation approaches in both time and space in computational cell biology (2017)
  8. Engblom, Stefan; Hellander, Andreas; Lötstedt, Per: Multiscale simulation of stochastic reaction-diffusion networks (2017)
  9. Lin, Zhongwei; Tropper, Carl; McDougal, Robert A.; Ishlam Patoary, Mohammand Nazrul; Lytton, William W.; Yao, Yiping; Hines, Michael L.: Multithreaded stochastic PDES for reactions and diffusions in neurons (2017)
  10. Meinecke, Lina: Multiscale modeling of diffusion in a crowded environment (2017)
  11. Sheng, Yin; Zeng, Zhigang: Synchronization of stochastic reaction-diffusion neural networks with Dirichlet boundary conditions and unbounded delays (2017)
  12. Blanc, Emilie; Engblom, Stefan; Hellander, Andreas; Lötstedt, Per: Mesoscopic modeling of stochastic reaction-diffusion kinetics in the subdiffusive regime (2016)
  13. Del Razo, Mauricio J.; Qian, Hong: A discrete stochastic formulation for reversible bimolecular reactions via diffusion encounter (2016)
  14. Dobramysl, Ulrich; Rüdiger, Sten; Erban, Radek: Particle-based multiscale modeling of calcium puff dynamics (2016)
  15. Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas: MOLNs: a cloud platform for interactive, reproducible, and scalable spatial stochastic computational experiments in systems biology using pyurdme (2016) ioport
  16. Meinecke, Lina; Engblom, Stefan; Hellander, Andreas; Lötstedt, Per: Analysis and design of jump coefficients in discrete stochastic diffusion models (2016)
  17. Meinecke, Lina; Lötstedt, Per: Stochastic diffusion processes on Cartesian meshes (2016)
  18. Flegg, Mark B.; Hellander, Stefan; Erban, Radek: Convergence of methods for coupling of microscopic and mesoscopic reaction-diffusion simulations (2015)
  19. Lötstedt, Per; Meinecke, Lina: Simulation of stochastic diffusion via first exit times (2015)
  20. Agbanusi, I. C.; Isaacson, S. A.: A comparison of bimolecular reaction models for stochastic reaction-diffusion systems (2014)

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