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Nested sampling for parameter inference in systems biology: application to an exemplar circadian model

<24> This article appeared in one of the principal computational systems biology journals. It presents the first application of nested sampling to a gene regulatory network model, showing that the method generates parameter moment estimates of comparable accuracy to Markov Chain Monte Carlo, but with an order of magnitude reduction in computation time. It shows that for circadian systems, longer, sparsely sampled timeseries are more informative than highly sampled timeseries. This is significant for designing maximally informative experiments for inferring circadian architectures. It has generated considerable interest since publication in July 2013, with over 1400 downloads by November.