Silk, D;
Kirk, PD;
Barnes, CP;
Toni, T;
Stumpf, MP;
(2014)
Model selection in systems biology depends on experimental design.
PLoS Computational Biology
, 10
(6)
, Article e1003650. 10.1371/journal.pcbi.1003650.
Preview |
Text
Model selection in systems biology depends on experimental design..pdf Download (1MB) | Preview |
Abstract
Experimental design attempts to maximise the information available for modelling tasks. An optimal experiment allows the inferred models or parameters to be chosen with the highest expected degree of confidence. If the true system is faithfully reproduced by one of the models, the merit of this approach is clear - we simply wish to identify it and the true parameters with the most certainty. However, in the more realistic situation where all models are incorrect or incomplete, the interpretation of model selection outcomes and the role of experimental design needs to be examined more carefully. Using a novel experimental design and model selection framework for stochastic state-space models, we perform high-throughput in-silico analyses on families of gene regulatory cascade models, to show that the selected model can depend on the experiment performed. We observe that experimental design thus makes confidence a criterion for model choice, but that this does not necessarily correlate with a model's predictive power or correctness. Finally, in the special case of linear ordinary differential equation (ODE) models, we explore how wrong a model has to be before it influences the conclusions of a model selection analysis.
| Type: | Article |
|---|---|
| Title: | Model selection in systems biology depends on experimental design |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1371/journal.pcbi.1003650 |
| Publisher version: | http://dx.doi.org/10.1371/journal.pcbi.1003650 |
| Language: | English |
| Additional information: | © 2014 Silk et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. http://creativecommons.org/licenses/by/4.0/ |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Cell and Developmental Biology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1432970 |
Loading...
Loading...Loading...Loading...Archive Staff Only
 |
View Item |
