title: Metabolic network modeling with model organisms.
abstract: Flux balance analysis (FBA) with genome-scale metabolic network models (GSMNM) allows systems level predictions of metabolism in a variety of organisms. Different types of predictions with different accuracy levels can be made depending on the applied experimental constraints ranging from measurement of exchange fluxes to the integration of gene expression data. Metabolic network modeling with model organisms has pioneered method development in this field. In addition, model organism GSMNMs are useful for basic understanding of metabolism, and in the case of animal models, for the study of metabolic human diseases. Here, we discuss GSMNMs of most highly used model organisms with the emphasis on recent reconstructions.
authors.affiliation: Program in Systems Biology, Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA, United States. Electronic address: lutfu.yilmaz@umassmed.edu.
authors.forename: L Safak
authors.initials: LS
authors.lastname: Yilmaz
authors.affiliation: Program in Systems Biology, Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA, United States. Electronic address: marian.walhout@umassmed.edu.
authors.forename: Albertha Jm
authors.initials: AJ
authors.lastname: Walhout
mesh_terms: D000818:Animals; D017360:Arabidopsis / Q000235:genetics / Q000378:metabolism; D001419:Bacteria; D004926:Escherichia coli / Q000235:genetics / Q000378:metabolism; D015870:Gene Expression; D016678:Genome; D006801:Humans; D053858:Metabolic Networks and Pathways / Q000235:genetics; D023421:Models, Animal; D008954:Models, Biological; D010944:Plants; D012441:Saccharomyces cerevisiae / Q000235:genetics / Q000378:metabolism