QSSPN: Dynamic Simulation of Molecular Interaction Networks

Describing Gene Regulation, Signalling and Whole-Cell Metabolism

in Human Cells.

Bioinformatics Advance Access published September 23, 2013

Systems Biology .P.Fisher, N.J.Plant, J.B.Moore and A.M.Kierzek* Faculty of Health and Medical Sciences, University of Surrey, G

uildford, Surrey GU2 7XH, UK. © The Author(s) 2013. Published by Oxford University Press. This is an Open Access article distributed under the terms of th

e Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits un

restricted reuse, distribution, and reproduction in any medium, provided the original work is prope

rly cited.

Contents

1 INTRODUCTION 2 METHODS 3 RESULTS 4 DISCUSSION

1 INTRODUCTION

2 METHODS

2.1 QSSPN algorithm 2.2 Monte Carlo sampling of token game

trajectories.

2.1 QSSPN algorithm

2.2 Monte Carlo sampling of token game trajectories.

3 RESULTS

3.1 General model of gene expression 3.2 Dynamic simulation of bile acid

homeostasis 3.3 Analysis of genotype-phenotype

relationship 3.4 Software and Model Distribution

3.1 General model of gene expression

3.2 Dynamic simulation of bile acid homeostasis

3.2 Dynamic simulation of bile acid homeostasis

3.3 Analysis of genotype-phenotype relationship

3.4 Software and Model Distribution

4 DISCUSSION

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