HIGHLIGHTS
- who: Ian Vernon from the Department of Mathematical Sciences, Durham University, South Road, LE Durham, UK have published the research work: Bayesian uncertainty analysis for complex systems biology models: emulation, global parameter searches and evaluation of gene functions, in the Journal: (JOURNAL)
- what: The multiple insights into the model's structure that this analysis provides are discussed. The authors demonstrate the power of the Bayesian emulation methodology by applying it to the hormonal crosstalk network in Arabidopsis root development. Specifically, the authors explore the model's 32-dimensional parameter space, and identify the set of . . .
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