Role of wet experiment design in data generation: from in vivo to in silico and back.

A thorough understanding of the in vivo kinetics of microorganisms requires the analysis of different data sets and therefore needs support from different sources of genome, transcriptome, proteome and metabolome data, as well as to generate new data in the laboratory to depict cell phenotypes in different scenarios. The value of dynamic metabolic data depends on the adequate design of wet experiments. In this paper a schematic representation of wet dynamic experiments to generate data is discussed. As a case study, the linking of the central metabolism with the carnitine secondary metabolism in E. coli is presented. The feed-back between the data generated and in silico modeling helps our understanding of the Escherichia coli expressed phenotype and permits new wet experiments to be designed to generate data concerning metabolic optimization.

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