We are pleased to announce that version 4.0.6 of MCell is now available for download!

It comes with a new, more efficient, implementation of MCell's simulation engine, native BioNetGen language support, and a versatile Python API that allows modeling of biological systems previously inaccessible and provides for integration with external simulators. Also the CellBlender plugin had been updated to work with Blender 2.93. You can download MCell4 with CellBlender here.

The 2022 Cell Modeling Workshop will be held as a virtual workshop from July 11th-15th, 2022. For more details, visit: 2022 Cell Modeling Workshop

The 2021 Cell Modeling Workshop will be held as a virtual workshop from July 12th-16th, 2021. For more details, visit: 2021 Cell Modeling Workshop

The 2020 Cell Modeling Workshop will be held as a virtual workshop from June 22nd-26th, 2020. For more details, visit: 2020 Cell Modeling Workshop

A new version of MCell is available from our Downloads page.

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.

The tutorials are the best way to learn about using MCell and CellBlender for new users. If you have a question about using MCell and CellBlender, feel free to ask it on our forums.

For all publications that make use of MCell, we ask that you the include the following acknowlegement:

MCell development is supported by the NIGMS-funded (P41GM103712) National Center for Multiscale Modeling of Biological Systems (MMBioS)

Also, please cite these three papers:

• 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 cells—cellular 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.