A Bayesian approach to targeted experiment design
Vanlier, J. (만든이), Tiemann, C.A. (만든이), Hilbers, P.A.J. (만든이), Van Riel, N.A.W. (만든이)
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
다운로드 가능한 기록 자료, English, 2012-04-15
Oxford University Press, 2012-04-15