Distributed Cell Biology Simulations with the E-Cell System

  • Masahiro Sugimoto
Part of the Molecular Biology Intelligence Unit book series (MBIU)

Abstract

Analytical techniques in computational cell biology such as kinetic parameter estimation, Metabolic Control Analysis (MCA) and bifurcation analysis require large numbers of repetitive simulation runs with different input parameters. The requirements for significant computational resources imposed by those analytical methods have led to an increasing interest in the use of parallel and distributed computing technologies.

We developed a Python-scripting environment that can execute the above mathematical analyses. Also, where possible, it automatically and transparently parallelizes them on either (1) stand-alone PCs, (2) shared-memory multiprocessor (SMP) servers, (3) cluster systems, or (4) a computational grid infrastructure. We named this environment E-Cell Session Manager (ESM). It involves user-friendly flat application program interfaces (APIs) for scripting and a pure object-oriented programming environment for sophisticated implementation of a user’s analysis.

In this chapter, fundamental concepts related to the design and the ESM architecture are introduced. We also describe an estimation of the parameters with some script examples executed on ESM.

Keywords

Genetic Algorithm Grid Infrastructure Metabolic Control Analysis Cluster Machine Kinetic Parameter Estimation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Landes Bioscience and Springer Science+Business Media, LLC 2013

Authors and Affiliations

  • Masahiro Sugimoto
    • 1
    • 2
  1. 1.Institute for Advanced BiosciencesKeio UniversityTsuruoka, YamagataJapan
  2. 2.Department of BioinformaticsMitsubishi Space Software Co. Ltd.Amagasaki, HyogoJapan

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