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Computational models are useful for quantitative elucidation of the dynamical behavior of biological systems. Oftentimes, several competing models (i.e., hypotheses) are proposed to describe the underlying molecular mechanisms of a biological system. Selecting the most representative model is imperative for obtaining meaningful quantitative insights into the dynamics of the system of interest. However, the discrimination between competing models poses a significant challenge due to heterogeneity that is intrinsic to biological systems. This letter demonstrates the effectiveness of a probabilistic approach to optimal experiment design for model discrimination in the presence of time-invariant cell-to-cell differences within a cell population. The JAK2/STAT5 signaling pathway, which is involved in proliferation and differentiation of hematopoietic stem cells, is used as a case study.
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Martin-Casas et al. (2016) studied this question.
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