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Related Experiment Video

Updated: Jun 17, 2026

Fabrication of a Multiplexed Artificial Cellular MicroEnvironment Array

Fabrication of a Multiplexed Artificial Cellular MicroEnvironment Array

Published on: September 7, 2018

CellMC--a multiplatform model compiler for the Cell Broadband Engine and x86.

Emmet Caulfield¹, Andreas Hellander

¹Department of Information Technology, Uppsala University, Box 337, SE-751 05, Uppsala, Sweden.

Bioinformatics (Oxford, England)

|December 10, 2009

Summary

CellMC compiles SBML models using a vectorized Gillespie's stochastic simulation algorithm (SSA) for efficient biochemical systems analysis. This software runs on Cell Broadband Engine (Cell/BE) and x86 PCs, accelerating stochastic modeling.

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Area of Science:

Computational Biology
Biochemistry
Systems Biology

Background:

Gillespie's stochastic simulation algorithm (SSA) is a key method for studying stochastic biochemical systems.
Specialized hardware like the Cell Broadband Engine (Cell/BE) offers potential for accelerating these simulations.
Existing tools may not fully leverage the capabilities of such architectures for biochemical modeling.

Purpose of the Study:

To develop a multiplatform SBML model compiler for efficient stochastic simulations.
To implement a vectorized version of Gillespie's SSA optimized for specialized architectures.
To provide a tool that runs on both Cell/BE and standard x86 PCs.

Main Methods:

Developed CellMC, a software tool that compiles Systems Biology Markup Language (SBML) models.
Implemented a vectorized approach to Gillespie's stochastic simulation algorithm (SSA).
Ensured compatibility with Cell Broadband Engine (Cell/BE) and x86 personal computers (PCs).

Main Results:

CellMC enables the compilation and execution of SBML models using a vectorized SSA.
The software is designed for high-performance computing on Cell/BE architectures.
It also runs effectively on widely available x86 PCs, offering broad accessibility.

Conclusions:

CellMC provides an efficient and accessible platform for stochastic modeling in biochemical systems.
Vectorized SSA implementation on Cell/BE and x86 architectures significantly enhances simulation performance.
The tool democratizes advanced computational biology techniques through multiplatform availability.