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  • CompuCell3D ( Software )

    We proudly announce third CompuCell3D Training Workshop that will be hosted by Biocomplexity Institute at Indiana University, May 2009. Exact date will be given soon . For more information please visit:


    Modeling the behavior of multi-cell biological systems using multi-scale approach is one of the goals behind CompuCel3D project.
    CompuCell3D was originally written to model morphogenesis, the process in embryonic development where cells cluster into patterns which eventually differentiate into organs, muscle or bone. Through integration of multiple mathematical models into a software implementation with easy to use XML based syntax scientists were able to build models within few hours as opposed to weeks when writing source code from scratch. compuCell3D is based on Glazier-graner-Hogeweg model (GGH) also known as the Cellular Potts Model (CPM).The model is capable of capturing key cellular behaviors: cell clustering as well as growth, division, death, intracellular adhesion, and volume and surface area constraints;

    In addition researchers may include partial differential equation models for external chemical fields which can model reaction-diffusion, and cell type automata to provide a method for categorizing cells by behavior into types and algorithms for changing cell type.
    These models can communicate to establish for example cellular reactions to external chemical fields such as secretion or resorption, and cellular responses such as chemotaxis and haptotaxis. Using scripting language (Python) users may build sophisticated intra-cellular models e.g. reaction-kinetics models, gene pathways etc that determine macroscopic properties of cells. Thus using CompuCell3D one can build truly multi-scale, multi-cell models.

    The Graphical User Interface CompuCellPlayer, built upon Qt, interactively visualizes these simulations in three dimensions and also provides the ability to switch to 2D cross sections in each dimension, and also the ability to alternate between chemical fields being visualized. Through this player you can easily pause a simulation to view results and restart again, and also use camera techniques such as zooming, rotating, translating and projecting to more easily view results. The Player uses Qt Threads to enable parallel execution with the CompuCell3D back end. Through the player you can save screenshots of a simulation and for long simulations the Player can be run in silent mode to improve performance, generating images every certain number of steps.

    CompuCell3D is an example of Problem Solving Environment (PSE) and has further reaching goals than narrowly specialized research code. In general, the PSE's have multiple requirements. It should be able to run simulations in three dimensions, it should be designed for performance and memory consumption due to the potential for large quantities of cells and superimposed fields, it should be flexible and extensible to allow for the addition of new cell behaviors or at a higher level, new models. Also, users will want to visualize cells and/or fields, check results, run benchmarks, pause the simulation and change parameter values and view results, etc.

    We provide all these features in a single package - CompuCell3D. Both source code and binaries are available for Windows, Linux and Mac OS X. For complete download selection please visit

    We make both tools available for the Linux and MacOS operating systems.

  • Molecular Dynamics Language ( Software )

    The Molecular Dynamics Language (MDL) is intended to allow users to represent molecular dynamics (MD) simulations at a high level. This includes the ability to interact directly with running simulations and prototype new integration schemes using several different methods, including both objects and functions which update position and velocity sets. The language builds upon Python and uses a set of SWIG-wrapped libraries from the software framework ProtoMol, developed in part to meet the heavy performance requirements of long-range force computations. Adding and testing new force evaluation algorithms are helped through the modular design of MDL, as well as new simulation protocols. The API includes functionality to access simulation data, input and output data in different files and formats, add data plots, add different types of forces to individual integrators, use existing integrators from the ProtoMol framework in Python, and convert data vectors into fast Numeric arrays. MDL is currently available for 32-bit Linux and Mac OS X.

  • ProtoMol ( Software )

    ProtoMol is an object-oriented, component based, framework for molecular dynamics (MD) simulations. The framework supports the CHARMM 19 and 28a2 force fields and is able to process PDB, PSF, XYZ and DCD trajectory files. It is designed for high flexibility, easy extendibility and maintenance, and high performance demands, including parallelization. The technique of multiple time-stepping is used to improve long-term efficiency. The use of fast electrostatic force evaluation algorithms like Ewald, particle Mesh Ewald (PME), and Multigrid (MG) summation further enhances performance. Longer time steps are possible using MOLLY, Langevin Molly and Hybrid Monte Carlo, Nose-Hoover, and Langevin integrators. Key Features of ProtoMol 3.0 (available Summer 2009): 1) Interface to OpenMM, an MD library with NVIDIA and ATI general purpose GPU support. OpenMM supports AMBER force fields and Generalized-Born implicit solvent. 2)Python bindings offered as MDLab, which allow for prototyping of high level sampling protocols, new integrators, and new force calculations in Python. 3) Coarse grained normal mode analysis (CNMA), which provides a scalable O(N9/5) time and O(N3/2) memory diagonalization. CNMA approximates low frequency modes very well. 4) Normal Mode Langevin (NML) dynamics, which uses CNMA to periodically compute low frequency bases for propagation of dynamics, while fast modes are minimized to their equilibrium position. NML allows timesteps of 100 fs and more for even small proteins (> 30 residues) with real speedups that are about a third of the timestep used. 5) Full checkpointing support, which simplifies use in distributed computing platforms such as Condor or Folding@Home.

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Last updated: 2013-09-30T16:18:45.917-04:00

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