Please use this identifier to cite or link to this item: https://doi.org/10.1016/S1570-7946(07)80192-1
DC FieldValue
dc.titleIdentifying synergistically switching pathways for multi-product strain improvement using multiobjective flux balance analysis
dc.contributor.authorSelvarasu, S.
dc.contributor.authorLee, D.-Y.
dc.contributor.authorA. Karimi, I.
dc.date.accessioned2014-06-17T07:42:42Z
dc.date.available2014-06-17T07:42:42Z
dc.date.issued2007
dc.identifier.citationSelvarasu, S.,Lee, D.-Y.,A. Karimi, I. (2007). Identifying synergistically switching pathways for multi-product strain improvement using multiobjective flux balance analysis. Computer Aided Chemical Engineering 24 : 1007-1012. ScholarBank@NUS Repository. <a href="https://doi.org/10.1016/S1570-7946(07)80192-1" target="_blank">https://doi.org/10.1016/S1570-7946(07)80192-1</a>
dc.identifier.isbn9780444531575
dc.identifier.issn15707946
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/64054
dc.description.abstractThe current work involves in silico analysis of metabolic network of E. coli, characterizing its pathways for the production of various industrially important metabolites including pyruvate, acetate, lactate, ethanol and various amino acids. Initially, the correlation among the flux distribution profiles for each objective has been investigated by resorting to a novel multiobjective optimization. Subsequently, we identified the genes which are significant for switching the metabolic pathways from one objective to another. Thus, the present analysis allows us to explore synergism among the metabolic pathways for different combinations of multi-products, providing a new insight into the behavior of the biological system. © 2007 Elsevier B.V. All rights reserved.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/S1570-7946(07)80192-1
dc.sourceScopus
dc.subjectgene target identification
dc.subjectMetabolic engineering
dc.subjectmultiobjective flux balance analysis
dc.subjectstrain improvement
dc.subjectsynergistic pathway
dc.typeArticle
dc.contributor.departmentCHEMICAL & BIOMOLECULAR ENGINEERING
dc.description.doi10.1016/S1570-7946(07)80192-1
dc.description.sourcetitleComputer Aided Chemical Engineering
dc.description.volume24
dc.description.page1007-1012
dc.identifier.isiutNOT_IN_WOS
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