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A Study of the Correlation Structure of Microarray Gene Expression Data Based on Mechanistic Modeling of Cell Population Kinetics

Publication at Faculty of Mathematics and Physics |
2020

Abstract

We consider the effect of heterogeneity on observed correlations between gene pairs within expression profiles. The effect of tissue heterogeneity on correlations is directly estimated for a simple two component model.

Then, a stochastic model of cell population kinetics is used to assess correlation effects for more complex mixtures. Finally, a mathematical model for correlation effects of subject-level heterogeneity is developed.