TR&D2: Cell modeling, with an emphasis on developing tools to handle spatial and molecular complexity inherent to neuronal signal transmission.


Prototype of CellBlender Interface The central window shows an animated visualization of a MCell simulation of vesicular release from an axon in the neuropil model. The visualization was rendered via our prototype Visualization and Analysis Module. The neurophil model itself was prepared using our prototype Geometry Construction Module.


Computer modeling and simulation is critical for understanding the massive and complex datasets on neurophysiological systems that emerge from present day research.

Modeling these systems presents a multiscale challenge because of the interplay between spatial and molecular complexity that occurs on multiple levels of organization, from macromolecular assemblies to synapse architecture to neural circuits. Major advances over the current state-of-the-art for computational tools are needed to fully address the complexity at all of these levels. In TR&D2, we will build on the powerful simulation capabilities we have already developed, supported by the TR&D1 activities that will enable the generation of qualitative and quantitative data on molecular events which complements those available from experiments. We will create expanded tools that will handle orders of magnitude greater spatial and molecular complexity than has been previously possible, and that are necessary to support the next generation of cellular microphysiology research. These tools will be accessible to nonspecialists, applicable to a wide range of biological problems, and free for use by our collaborators and the scientific community.


Our technology development builds on MCell, our general purpose Monte Carlo simulator of biochemical interactions with realistic spatial organization. In development since 1995, MCell is a mature simulation tool with advanced capabilities to model the diffusion of and reactions between volume and surface molecules within arbitrary 3D geometries. The MCell development team includes the Faeder lab at the University of Pittsburgh, the Sejnowski lab at the Salk Institute, and the Biomedical Group at Pittsburgh Supercomputing Center.

Driven by the needs of our DBPs, we focus our efforts on three areas:

  • Development of an advanced modeling framework called CellBlender with a graphical interface for specifying, simulating, and analyzing MCell models, including rule-based specification of molecular interactions
  • Implementation of novel simulation algorithms and capabilities in MCell to handle spatial and molecular complexity
  • Parallelization of MCell for use on a wide range of hardware architectures