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dc.contributor.authorSegrè, Danielen_US
dc.contributor.authorPaschalidis, Ioannis Ch.en_US
dc.contributor.authorZhao, Qien_US
dc.contributor.authorStettner, Arion I.en_US
dc.contributor.authorReznik, Eden_US
dc.date.accessioned2016-09-30T01:15:59Z
dc.date.available2016-05-23
dc.date.available2016-09-30T01:15:59Z
dc.date.issued2016-05
dc.identifier.citationQi Zhao, Arion I Stettner, Ed Reznik, Ioannis Ch Paschalidis, Daniel Segrè. 2016. "Mapping the landscape of metabolic goals of a cell." Genome Biology, Volume 17, Issue 1.
dc.identifier.issn1474-760X
dc.identifier.urihttps://hdl.handle.net/2144/18023
dc.description.abstractGenome-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.en_US
dc.description.sponsorshipMURI W911NF-12-1-0390 - Army Research Office (US); MURI W911NF-12-1-0390 - Army Research Office (US); 5R01GM089978-02 - National Institutes of Health (US); IIS-1237022 - National Science Foundation (US); DE-SC0012627 - U.S. Department of Energy; HR0011-15-C-0091 - Defense Sciences Office, DARPA; National Institutes of Health; R01GM103502; 5R01DE024468; 1457695 - National Science Foundationen_US
dc.language.isoen_US
dc.publisherBioMed Centralen_US
dc.relation.ispartofGenome Biology
dc.relation.ispartofseriesGenome Biology: v. 17, no. 1;
dc.rightsAttribution 4.0 Internationalen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectFlux balance analysisen_US
dc.subjectGenome-scale stoichiometric modelsen_US
dc.subjectInverse optimizationen_US
dc.subjectMetabolic networksen_US
dc.subjectObjective functionsen_US
dc.subjectBioinformaticsen_US
dc.titleMapping the landscape of metabolic goals of a cellen_US
dc.typeArticleen_US
dc.identifier.doi10.1186/s13059-016-0968-2
pubs.notesEmbargo: No embargoen_US
pubs.organisational-group/Boston Universityen_US
pubs.organisational-group/Boston University/College of Arts & Sciencesen_US
pubs.organisational-group/Boston University/College of Arts & Sciences/Department of Biologyen_US
pubs.organisational-group/Boston University/College of Engineeringen_US
pubs.organisational-group/Boston University/College of Engineering/Department of Electrical & Computer Engineeringen_US
dc.date.online2016-05-23


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Attribution 4.0 International
Except where otherwise noted, this item's license is described as Attribution 4.0 International