### Abstract

Many useful applications of simulation in computational cell biology, e.g. kinetic parameter estimation, Metabolic Control Analysis (MCA), and bifurcation analysis, require a large number of repetitive runs with different input parameters. The heavy requirements imposed by these analysis methods on computational resources has led to an increased interest in parallel- and distributed computing technologies. We have developed a scripting environment that can execute, and where possible, automatically parallelize those mathematical analysis sessions transparently on any of (1) single-processor workstations, (2) Shared-memory Multiprocessor (SMP) servers, (3) workstation clusters, and (4) computational grid environments. This computational framework, E-Cell SessionManager (ESM), is built upon E-Cell System Version 3, a generic software environment for the modeling, simulation, and analysis of whole-cell scale biological systems. Here we introduce the ESM architecture and provide results from benchmark experiments that addressed 2 typical computationally intensive biological problems, (1) a parameter estimation session of a small hypothetical pathway and (2) simulations of a stochastic E. coli heat-shock model with different random number seeds to obtain the statistical characteristics of the stochastic fluctuations.

Original language | English |
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Pages (from-to) | 20-31 |

Number of pages | 12 |

Journal | Lecture Notes in Bioinformatics (Subseries of Lecture Notes in Computer Science) |

Volume | 3370 |

DOIs | |

Publication status | Published - 2005 Jan 1 |

Event | First International Workshop on Life Science Grid, LSGRID 2004: Grid Computing in Life Science - Kanazawa, Japan Duration: 2004 May 31 → 2004 Jun 1 |

### ASJC Scopus subject areas

- Theoretical Computer Science
- Computer Science(all)

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## Cite this

*Lecture Notes in Bioinformatics (Subseries of Lecture Notes in Computer Science)*,

*3370*, 20-31. https://doi.org/10.1007/978-3-540-32251-1_3