Toggle Main Menu Toggle Search

Open Access padlockePrints

The Newcastle University research output collection, currently available on ePrints, will shortly be moving to a new open repository platform, Figshare. To prepare for the data migration we have paused adding new content to ePrints, and will resume once the new repository is launched. During this time you will continue to have access to ePrints (but no new content will appear). We will share updates here when available.

Automatic Parameterisation of Stochastic Petri Net Models of Biological Networks

Lookup NU author(s): Oliver Shaw, Dr Jason StegglesORCiD, Professor Anil Wipat

Downloads

Full text for this publication is not currently held within this repository. Alternative links are provided below where available.

Abstract

Stochastic simulations are able to capture the fine grain behaviour and randomness of outcome of biological networks not captured by deterministic techniques. As such they are becoming an increasingly important tool in the biological community. However, current efforts in the stochastic simulation of biological networks are hampered by two main problems: firstly the lack of complete knowledge of kinetic parameters; and secondly the computational cost of the simulations. In this paper we investigate these problems using the framework of stochastic Petri nets. We present a new stochastic Petri net simulation tool NASTY which allows large numbers of stochastic simulations to be carried out in parallel. We then begin to address the important problem of incomplete knowledge of kinetic parameters by developing a distributed genetic algorithm, based on NASTY's simulation engine, to parameterise stochastic networks. Our algorithm is able to successfully estimate kinetic parameters to replicate a system's behaviour and we illustrate this by presenting a case study in which the kinetic parameters are derived for a stochastic model of the stress response pathway in the bacterium E.coli. © 2006.

Publication metadata

Author(s): Shaw O, Steggles J, Wipat A

Editor(s): N. Thomas

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: 2nd International Workshop on the Practical Application of Stochastic Modeling (PASM 2005)

Year of Conference: 2005

Pages: 111-129

ISSN: 1571-0661

Publisher: Electronic Notes in Theoretical Computer Science: Elsevier

URL: http://dx.doi.org/10.1016/j.entcs.2006.03.015

DOI: 10.1016/j.entcs.2006.03.015

Share