Genome-Scale Reconstruction of Escherichia coli's Transcriptional and Translational Machinery: A Knowledge Base, Its Mathematical Formulation, and Its Functional Characterization
Figure 5
Integration of ‘-omics’ data into ‘E-matrix’ as reaction constraints.
(A) This schema illustrates the types of high-throughput data (HT, red boxes) or low-throughput data (LT, blue boxes) that can be directly integrated with the ‘E-matrix’ as it accounts for the different macromolecules measured in these data sets. In contrast, the integration of regulatory information would require the formulation of the regulatory network in matrix format (‘Operon’ or ‘O’-matrix). Furthermore, the metabolic network, here represented as ‘M-matrix’, would enable the mapping of fluxomic, metabolomic and phenomic data. (B–D) Absolute flux span in ‘E-matrix’ while incorporating successively more complex constraints (see text for more details). (B) LB-medium specific constraints were applied on exchange reactions. (C) The upper bounds of stable RNA transcription initiation reactions were constrained. (D) Additional constraints on upper bound of mRNA degradation flux rates were applied.