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10.1186/s13059-016-0968-2 http://scihub22266oqcxt.onion/10.1186/s13059-016-0968-2 C4878026!4878026!27215445     free     free     free       Genome+Biol 2016 ; 17 (ä): ä Nephropedia Template TP {{tp|p=27215445|t=2016. Mapping the landscape of metabolic goals of a cell |pdf=|usr=}}{{27215445}} gab.com Text Mapping the landscape of metabolic goals of a cell JO: Genome Biol http://www.kidney.de/pget.php?&tw=1&pmid=27215445 #FOAvip Genome-scale flux balance models of metabolism provide testable predictions of all metabolic rates in an organism, by assuming that the cell is optimizing a metabolic goal known as the objective function. We introduce an efficient inverse flux balance analysis (invFBA) approach, based on linear programming duality, to characterize the space of possible objective functions compatible with measured fluxes. After testing our algorithm on simulated E. coli data and time-dependent S. oneidensis fluxes inferred from gene expression, we apply our inverse approach to flux measurements in long-term evolved E. coli strains, revealing objective functions that provide insight into metabolic adaptation trajectories.Electronic supplementary material: The online version of this article (doi:10.1186/s13059-016-0968-2) contains supplementary material, which is available to authorized users. Twit Text FOAVip Mapping the landscape of metabolic goals of a cell ????Genome Biol http://www.kidney.de/pget.php?&tw=1&pmid=27215445 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27215445 #FOAvip English Wikipedia <ref>{{Cite pmid|27215445}}</ref> Mapping the landscape of metabolic goals of a cell #MMPMID27215445 Zhao Q; Stettner AI; Reznik E; Paschalidis IC; Segrč D Genome Biol 2016[]; 17 (ä): ä PMID27215445show ga Genome-scale flux balance models of metabolism provide testable predictions of all metabolic rates in an organism, by assuming that the cell is optimizing a metabolic goal known as the objective function. We introduce an efficient inverse flux balance analysis (invFBA) approach, based on linear programming duality, to characterize the space of possible objective functions compatible with measured fluxes. After testing our algorithm on simulated E. coli data and time-dependent S. oneidensis fluxes inferred from gene expression, we apply our inverse approach to flux measurements in long-term evolved E. coli strains, revealing objective functions that provide insight into metabolic adaptation trajectories.Electronic supplementary material: The online version of this article (doi:10.1186/s13059-016-0968-2) contains supplementary material, which is available to authorized users. äMapping the landscape of metabolic goals of a cell (epmc).pdf DeepDyve Pubget Overpricing