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Accelerating Gene Regulatory Network Modeling Using Grid-Based Simulation

Department of Electrical and Computer Engineering University of Tennessee-Knoxville, jmccoll2{at}utk.edu

Gregory D. Peterson

Department of Electrical and Computer Engineering, University of Tennessee-Knoxville

Chris D. Cox

Department of Civil and Environmental Engineering, Center for Environmental Biotechnology, University of Tennessee-Knoxville

Michael L. Simpson

Molecular Scale Engineering and Nanoscale Technologies Research Group, Oak Ridge National Laboratory, Department of Material Science and Engineering, Center for Environmental Biotechnology, University of Tennessee-Knoxville

Modeling gene regulatory networks has, in some cases, enabled biologists to predict cellular behavior long before such behavior can be experimentally validated. Unfortunately, the extent to which biologists can take advantage of these modeling techniques is limited by the computational complexity of gene regulatory network simulation algorithms. This study presents a new platform-independent, grid-based distributed computing environment that accelerates biological model simulation and, ultimately, development. Applying this environment to gene regulatory network simulation shows a significant reduction in execution time versus running simulation jobs locally. To analyze this improvement, a performance model of the distributed computing environment is built. Although this grid-based system was specifically developed for biological simulation, the techniques discussed are applicable to a variety of simulation performance problems.

Key Words: Computational biology • grid-based simulation • gene regulatory networks • performance model

SIMULATION, Vol. 80, No. 4-5, 231-241 (2004)
DOI: 10.1177/0037549704045051


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