Show simple item record

dc.contributor.authorLun, Desmond S
dc.contributor.authorRockwell, Graham
dc.contributor.authorGuido, Nicholas
dc.contributor.authorBaym, Michael Hartmann
dc.contributor.authorKelner, Jonathan A
dc.contributor.authorBerger, Bonnie
dc.contributor.authorGalagan, James E
dc.contributor.authorChurch, George McDonald
dc.date.accessioned2011-05-11T02:02:36Z
dc.date.issued2009
dc.identifier.citationLun, Desmond S., Graham Rockwell, Nicholas J. Guido, Michael Baym, Jonathan A. Kelner, Bonnie Berger, James E. Galagan, and George M. Church. 2009. Large-scale identification of genetic design strategies using local search. Molecular Systems Biology 5: 296.en_US
dc.identifier.issn1744-4292en_US
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:4887111
dc.description.abstractIn the past decade, computational methods have been shown to be well suited to unraveling the complex web of metabolic reactions in biological systems. Methods based on flux–balance analysis (FBA) and bi-level optimization have been used to great effect in aiding metabolic engineering. These methods predict the result of genetic manipulations and allow for the best set of manipulations to be found computationally. Bi-level FBA is, however, limited in applicability because the required computational time and resources scale poorly as the size of the metabolic system and the number of genetic manipulations increase. To overcome these limitations, we have developed Genetic Design through Local Search (GDLS), a scalable, heuristic, algorithmic method that employs an approach based on local search with multiple search paths, which results in effective, low-complexity search of the space of genetic manipulations. Thus, GDLS is able to find genetic designs with greater in silico production of desired metabolites than can feasibly be found using a globally optimal search and performs favorably in comparison with heuristic searches based on evolutionary algorithms and simulated annealing.en_US
dc.language.isoen_USen_US
dc.publisherNature Publishing Groupen_US
dc.relation.isversionofdoi:10.1038/msb.2009.57en_US
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC2736654/pdf/en_US
dash.licenseLAA
dc.titleLarge-scale identification of genetic design strategies using local searchen_US
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden_US
dc.relation.journalMolecular Systems Biologyen_US
dash.depositing.authorGuido, Nicholas
dc.date.available2011-05-11T02:02:36Z
dash.affiliation.otherHMS^Geneticsen_US
dash.affiliation.otherSPH^Immunology and Infectious Diseases TPHen_US
dash.affiliation.otherHMS^Health Sciences and Technologyen_US
dash.affiliation.otherHMS^Geneticsen_US
dc.identifier.doi10.1038/msb.2009.57*
dash.contributor.affiliatedGuido, Nicholas
dash.contributor.affiliatedGalagan, James E.
dash.contributor.affiliatedRockwell, G
dash.contributor.affiliatedBaym, Michael
dash.contributor.affiliatedChurch, George


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record