Snoopy\u2019s hybrid simulator: a tool to construct and simulate hybrid biological models

Mostafa Herajy,Fei Liu,Monika Heiner,Christian Rohr

doi:10.1186/s12918-017-0449-6

Abstract

BackgroundHybrid simulation of (computational) biochemical reaction networks, which combines stochastic and deterministic dynamics, is an important direction to tackle future challenges due to complex and multi-scale models. Inherently hybrid computational models of biochemical networks entail two time scales: fast and slow. Therefore, it is intricate to efficiently and accurately analyse them using only either deterministic or stochastic simulation. However, there are only a few software tools that support such an approach. These tools are often limited with respect to the number as well as the functionalities of the provided hybrid simulation algorithms.ResultsWe present Snoopy’s hybrid simulator, an efficient hybrid simulation software which builds on Snoopy, a tool to construct and simulate Petri nets. Snoopy’s hybrid simulator provides a wide range of state-of-the-art hybrid simulation algorithms. Using this tool, a computational model of biochemical networks can be constructed using a (coloured) hybrid Petri net’s graphical notations, or imported from other compatible formats (e.g. SBML), and afterwards executed via dynamic or static hybrid simulation.ConclusionSnoopy’s hybrid simulator is a platform-independent tool providing an accurate and efficient simulation of hybrid (biological) models. It can be downloaded free of charge as part of Snoopy from http://www-dssz.informatik.tu-cottbus.de/DSSZ/Software/Snoopy.

Highlights

Hybrid simulation of biochemical reaction networks, which combines stochastic and deterministic dynamics, is an important direction to tackle future challenges due to complex and multi-scale models
Snoopy’s hybrid simulator provides a graphical and convenient way to construct hybrid models Before using Snoopy’s hybrid simulator, a model needs to be constructed by specifying reactions, species, stoichiometries, kinetic rates, etc
We present two methods that permit the construction of hybrid models in Snoopy

Summary

Introduction

Hybrid simulation of (computational) biochemical reaction networks, which combines stochastic and deterministic dynamics, is an important direction to tackle future challenges due to complex and multi-scale models. There are only a few software tools that support such an approach These tools are often limited with respect to the number as well as the functionalities of the provided hybrid simulation algorithms. Stochastic simulation algorithms (SSA) are often referred to as computationally inefficient as they may consume much runtime to accomplish the discrete and individual firing of reactions. They can be used to simulate models with a moderate amount of reactions that do not fire too frequently, since, increasing the number of reactions could at the same time increase the number of stochastic events.

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