Accession Number:

ADA480737

Title:

Stochastic Simulations of Cellular Biological Processes

Descriptive Note:

Conference paper

Corporate Author:

AIR FORCE RESEARCH LAB WRIGHT-PATTERSON AFB OH

Report Date:

2007-06-01

Pagination or Media Count:

10.0

Abstract:

INTRODUCTION From a systems engineering point of view, cells consist of a complex set of nested, nonlinear control systems dominated by feed-back and feed-forward loops. The more complex the system is, the more important are the issues concerning the robustness and parameter optimization, therefore modeling and simulations are important for both engineering and reverse-engineering of biosystems. OBJECTIVE At the functional level, all biological processes in cells can be represented as a series of biochemical reactions. Since such reactions are stochastic in nature, the user must run thousands of simulations to characterize the ensemble behavior of biological systems. We developed a software package called Biomolecular Network Simulator BNS to model and simulate complex biomolecular reaction networks using High Performance Computing HPC. METHODOLOGY The Biomolecular Network Simulator uses the Gillespie stochastic algorithm to simulate the evolution of a system of biochemical reactions. The BNS code is a combination of MATLAB and C-coded modules. This combination allows one to use the interactive features and visualization tools of MATLAB, while achieving high speed for the computationally intensive part of the software. The software is parallelized with the MPI library to run on multiprocessor architectures. RESULT The Biomolecular Network Simulator consists of two sets of tools for simulations of the system and for the analysis of simulation results. The Graphical User Interface of BNS allows users to easily set parameters for the model and simulations and to select analysis method. Multiple types of post-simulation analyses are available. SIGNIFICANCE TO DoD The Developed software allows DoD scientists to build, simulate and analyze complex cellular biomolecular networks utilizing the capacities of HPC. It provides the foundational capability to design and integrate biological constructs into a new generation of biotechnology products.

Subject Categories:

  • Biochemistry
  • Statistics and Probability
  • Computer Programming and Software

Distribution Statement:

APPROVED FOR PUBLIC RELEASE