MCell and CellBlender development is supported by the NIGMS-funded (P41GM103712) Multiscale Modeling of Biological Systems (MMBioS) Center established by the Department of Computational and Systems Biology at the University of Pittsburgh, the Pittsburgh Supercomputing Center, the Computational Neurobiology Laboratory at the Salk Institute and Carnegie Mellon University.
- Stiles, JR, et al. (1996). Miniature endplate current rise times <100 μs from improved dual recordings can be modeled with passive acetylcholine diffusion from a synaptic vesicle. Proc. Natl. Acad. Sci. USA 93:5747-5752.
- Stiles, JR, and Bartol, TM. (2001). Monte Carlo methods for simulating realistic synaptic microphysiology using MCell. In: Computational Neuroscience: Realistic Modeling for Experimentalists, ed. De Schutter, E. CRC Press, Boca Raton, pp. 87-127.
- Kerr R, Bartol TM, Kaminsky B, Dittrich M, Chang JCJ, Baden S, Sejnowski TJ, Stiles JR. (2009). Fast Monte Carlo Simulation Methods for Biological Reaction-Diffusion Systems in Solution and on Surfaces. SIAM J. Sci. Comput., 30(6):3126-3149.
Cells are tightly packed with structures and molecules that carry out the day-to-day operations of living. Understanding how cellular design dictates function is essential to understanding life and disease, in the brain, heart, or elsewhere. MCell (Monte Carlo cell) is a program that uses spatially realistic 3-D cellular models and specialized Monte Carlo algorithms to simulate the movements and reactions of molecules within and between cellscellular microphysiology.
Model design, editing, and visualization are integral to microphysiological simulations. CellBlender is an addon for Blender 2.6-2.7x that allows users to create computational cell biology models for use in MCell. In addition, it is used to visualize MCell simulation results, including the locations and states of participating meshes and molecules.