Discrete Event Simulation

The Oxford English Dictionary describes simulation as: "The technique of imitating the behavior of some situation or system (economic, mechanical, etc.) by means of an analogous model, situation, or apparatus, either to gain information more conveniently or to train personnel." 

Discrete event simulation (DES) has been used as a tool for simulation complex systems in communication networks, transportation and logistic systems as well as complex dynamic systems like aircraft design and flight simulators. More on DES can be found here.

Our approach in studying the dynamics of complex biological processes revolves around building a discrete event simulator which simulates the various complex interactions which occur at different time scales in a cellular process. Based on stochastic models for different biological modules, we link the modules in the simulator and drive the in silico experiment based on "biological events". The dynamic behavior of various system resources and outputs are captured by the simulator in a temporal domain. 

                                           Simulation Methodology Overview

 Our current work is focused on two projects :

• iSimBioSys  : Developing a software framework for a discrete event simulator for complex biological system. The software, called iSimBioSys, is being currently developed for modeling the dynamics of gene regulatory pathways in bacterial cells.  More...

• HimSim : This a hybrid simulation approach which captures the interactive dynamics of gene regulatory and metabolic networks in bacterial cells, each operating at different temporal scales, working in tandem to choreograph the complex dance of  bacterial cell behaviors.  More..

iSimBioSys

Our Discrete Event Simulation Framework is called iSimBioSys.  It is a Java 1.5 based platform having a multi-threaded Simulation Engine with a Swing based graphical user interface. iSimBioSys  is currently in version 1.0. The features supported by iSimBioSys 1.0 are

•  Simulation of multiple gene regulatory pathways involved in  Salmonella pathogenesis.

• Real-time graphical trace of the system dynamics 

• User interface to define 'in silico' experimental parameters

Recently,  iSimBioSys 1.0 has been used to generate results for the expression dynamics of the PhoPQ pathway, details of which can be found in publications.. Some screenshots of the simulation are here.

                                   

   phoPQ gene regulatory network               iSimBioSys v1.0 User Interface              Effect of Mg diffusion rate on phoPQ  network

 

                                                                                         

  Real time dynamics of resource states             Enhanced UI for capturing real time dynamics of resource states (v1.1)

                                                  

    CPU and memory usage monitor                                                 CPU and memory usage in real time

• Some parameters used in the simulation are reported here, with resource parameters here, and gene list (here).

•  The public of publications related to phoPQ regulatory pathway in Salmonella Typhimurium used for knowledge extraction can be found here.

Our poster presentation at CSB 2005 on iSimBioSys is here.

New!  Also a short video clip of iSimBioSys in action here!

HimSim

One of the fundamental challenges in developing genome-scale system wide models and simulations for biological processes is the difference in time scales of the various molecular networks participating in the system. This problem of "stiffness" has been identified in system of rate-based differential equations and techniques have been developed for circumventing the time-scale impedance mismatch. The problem increases manifold in capturing system wide dynamics of a complex biological process.

In this project, we focus on developing a hybrid simulation platform which bridges the temporal gap between different networks and studies the system dynamics at a computational feasible scale. Specifically,  we are focusing on study the cascading effects of the interaction of metabolic gene regulatory networks and metabolic networks in bacterial cells. The role of regulatory networks on metabolic phenomics have been well studied in the community. Flux Balance Analysis (FBA)  techniques have been hugely successful in studying the behavior of large scale metabolic networks. Enhanced FBA models, which capture the gene regulatory effects as boolean input signals have also been captured in [1].

                    Effect of external signal on interaction of gene regulatory and metabolic reaction pathways in E.Coli                  

In the hybrid simulation, we integrate FBA based metabolic reaction network analysis along with DES based analysis of metabolic gene regulatory networks (as done in iSimBioSys ) to capture the cascading effects of their interactions with changes in actual environmental conditions. The DES simulates the regulatory network dynamics with the FBA module providing the metabolic dynamics to the system. A high level view of the hybrid simulation technique is captured below. More details to follow soon as part of poster presentation of HimSim at ICSB 2006.

                                                              Hybrid Simulation Framework