Hybrid Approaches: Integration of Gene Expression data into a GEM model

 

Following the introduction of GEM Models and the high-throughput approaches for extracting genome-wide expression pattern of a cell (e.g. DNA microarray, ChIP-Seq and RNA-Seq), the new challenge for a better prediction of the metabolic activities of different cells appeared; how gene expression data can be integrated into GEM models. The conflation of genetic expression data and GEM models leads to a better and deeper understanding of the occurrence of certain changes in gene expression under different conditions.
First, Covert and Palsson addressed this issue by Boolean approach in 2002.