English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

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.

Discrimination Between Competing Model Structures of Biological Systems in the Presence of Population Heterogeneity