A Bayesian approach to targeted experiment design
Vanlier, J. (製作者), Tiemann, C.A. (製作者), Hilbers, P.A.J. (製作者), Van Riel, N.A.W. (製作者)
Motivation: Systems biology employs mathematical modelling to further our understanding of biochemical pathways. Since the amount of experimental data on which the models are parameterized is often limited, these models exhibit large uncertainty in both parameters and predictions. Statistical methods can be used to select experiments that will reduce such uncertainty in an optimal manner. However, existing methods for optimal experiment design (OED) rely on assumptions that are inappropriate when data are scarce considering model complexity
ダウンロード可能なアーカイブ資料, English, 2012-04-15
Oxford University Press, 2012-04-15