MCELL

MCell is a modeling tool for realistic simulation of cellular signaling in the complex 3-D subcellular microenvironment in and around living cells -- what we call cellular microphysiology. At such small subcellular scales the familiar macroscopic concept of concentration is not useful and stochastic behavior dominates. MCell uses highly optimized Monte Carlo algorithms to track the stochastic behavior of discrete molecules in space and time as they diffuse and interact with other discrete effector molecules (e.g. ion channels, enzymes, transporters) heterogeneously distributed within the 3-D geometry of the subcellular environment. (Source: http://www.psc.edu/)


References in zbMATH (referenced in 22 articles )

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  1. Bouchnita, Anass; Hellander, Stefan; Hellander, Andreas: A 3D multiscale model to explore the role of EGFR overexpression in tumourigenesis (2019)
  2. Montes, Jesús; LaTorre, Antonio; Muelas, Santiago; Merchán-Pérez, Ángel; Peña, José M.: Comparative study of metaheuristics for the curve-fitting problem: modeling neurotransmitter diffusion and synaptic receptor activation (2015)
  3. Erban, Radek (ed.); Othmer, Hans G. (ed.): Editorial: Special issue on stochastic modelling of reaction-diffusion processes in biology (2014)
  4. Erban, Radek; Flegg, Mark B.; Papoian, Garegin A.: Multiscale stochastic reaction-diffusion modeling: application to actin dynamics in filopodia (2014)
  5. Karamitros, M.; Luan, S.; Bernal, M. A.; Allison, J.; Baldacchino, G.; Davidkova, M.; Francis, Z.; Friedland, W.; Ivantchenko, V.; Ivantchenko, A.; Mantero, A.; Nieminem, P.; Santin, G.; Tran, H. N.; Stepan, V.; Incerti, S.: Diffusion-controlled reactions modeling in Geant4-DNA (2014)
  6. Ma, Yan; Gong, Bin; Sugihara, Ryo; Gupta, Rajesh: Energy-efficient deadline scheduling for heterogeneous systems (2012)
  7. Buti, F.; Cacciagrano, D.; Corradini, F.; Merelli, E.; Tesei, L.; Pani, M.: Bone remodelling in \textscBioShape (2010)
  8. Fange, David; Berg, Otto G.; Sjöberg, Paul; Elf, Johan: Stochastic reaction-diffusion kinetics in the microscopic limit (2010)
  9. Ribeiro, Andre S.: Stochastic and delayed stochastic models of gene expression and regulation (2010)
  10. John, Mathias; Ewald, Roland; Uhrmacher, Adelinde M.: A spatial extension to the (\pi) calculus (2008)
  11. Kerr, Rex A.; Bartol, Thomas M.; Kaminsky, Boris; Dittrich, Markus; Chang, Jen-Chien Jack; Baden, Scott B.; Sejnowski, Terrence J.; Stiles, Joel R.: Fast Monte Carlo simulation methods for biological reaction-diffusion systems in solution and on surfaces (2008)
  12. Miller, David J.; Ghosh, Avijit: A fully adaptive reaction-diffusion integration scheme with applications to systems biology (2007)
  13. Derbal, Youcef: Entropic grid scheduling (2006) ioport
  14. Derbal, Youcef: A probabilistic scheduling heuristic for computational grids (2006)
  15. Derbal, Youcef: Entropic grid scheduling (2006)
  16. Farnell, L.; Gibson, W. G.: Monte Carlo simulation of diffusion in a spatially nonhomogeneous medium: A biased random walk on an asymmetrical lattice (2005)
  17. Bennett, Max R.; Farnell, L.; Gibson, W. G.; Blair, D.: A quantitative description of the diffusion of noradrenaline in the media of blood vessels following its release from sympathetic varicosities (2004)
  18. Farnell, L.; Gibson, W. G.: Monte Carlo simulation of diffusion in a spatially nonhomogeneous medium: Correction to the Gaussian steplength (2004)
  19. Krishnan, Arun: A survey of life sciences applications on the grid (2004)
  20. Tao, L.; Nicholson, C.: Maximum geometrical hindrance to diffusion in brain extracellular space surrounding uniformly spaced convex cells (2004)

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