### 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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Title of host publication | Lecture Notes in Bioinformatics (Subseries of Lecture Notes in Computer Science) |

Editors | A. Konagaya, K. Satou |

Pages | 20-31 |

Number of pages | 12 |

Volume | 3370 |

Publication status | Published - 2005 |

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

### Other

Other | First International Workshop on Life Science Grid, LSGRID 2004: Grid Computing in Life Science |
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Country | Japan |

City | Kanazawa |

Period | 04/5/31 → 04/6/1 |

### Fingerprint

### ASJC Scopus subject areas

- Biochemistry, Genetics and Molecular Biology (miscellaneous)
- Computer Science (miscellaneous)
- Computer Science(all)
- Biochemistry, Genetics and Molecular Biology(all)
- Theoretical Computer Science

### Cite this

*Lecture Notes in Bioinformatics (Subseries of Lecture Notes in Computer Science)*(Vol. 3370, pp. 20-31)

**Distributed cell biology simulations with E-Cell system.** / Sugimoto, Masahiro; Takahashi, Kouichi; Kitayama, Tomoya; Ito, Daiki; Tomita, Masaru.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Lecture Notes in Bioinformatics (Subseries of Lecture Notes in Computer Science).*vol. 3370, pp. 20-31, First International Workshop on Life Science Grid, LSGRID 2004: Grid Computing in Life Science, Kanazawa, Japan, 04/5/31.

}

TY - GEN

T1 - Distributed cell biology simulations with E-Cell system

AU - Sugimoto, Masahiro

AU - Takahashi, Kouichi

AU - Kitayama, Tomoya

AU - Ito, Daiki

AU - Tomita, Masaru

PY - 2005

Y1 - 2005

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=26444540417&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=26444540417&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:26444540417

VL - 3370

SP - 20

EP - 31

BT - Lecture Notes in Bioinformatics (Subseries of Lecture Notes in Computer Science)

A2 - Konagaya, A.

A2 - Satou, K.

ER -