IOMA (Integrative Omics Metabolic Analysis)
IOMA quantitatively integrates proteomic and metabolomic data with
genome-scale metabolic models to predict metabolic flux distributions. The
method is formulated as a quadratic programming (QP) problem that seeks a
steady-state flux distribution in which flux through reactions with
measured proteomic and metabolomic data, is as consistent as possible with
kinetically-derived flux estimations. [implementation]
Integrating Quantitative Proteomics and Metabolomics with a Genome-scale Metabolic Network Model.
K. Yizhak, T. Benyamini, W. Liebermeister, E. Ruppin, T. Shlomi