%0 Journal Article %1 Curran2012Using %A Curran, Kathleen A. %A Crook, Nathan C. %A Alper, Hal S. %B Methods in Molecular Biology %C New York, NY %D 2012 %I Springer New York %J Methods in molecular biology (Clifton, N.J.) %K flux-analysis metabolic-engineering %P 197--216 %R 10.1007/978-1-61779-483-4\_13 %T Using flux balance analysis to guide microbial metabolic engineering. %U http://dx.doi.org/10.1007/978-1-61779-483-4\_13 %V 834 %X Metabolic engineers modify biological systems through the use of modern molecular biology tools in order to obtain desired phenotypes. However, due to the extreme complexity and interconnectedness of metabolism in all organisms, it is often difficult to a priori predict which changes will yield the optimal results. Flux balance analysis (FBA) is a mathematical approach that uses a genomic-scale metabolic network models to afford in silico prediction and optimization of metabolic changes. In particular, a genome-scale approach can help select gene targets for knockout and overexpression. This approach can be used to help expedite the strain engineering process. Here, we give an introduction to the use of FBA and provide details for its implementation in a microbial metabolic engineering context. %& 13 %@ 978-1-61779-482-7

@article{Curran2012Using, abstract = { Metabolic engineers modify biological systems through the use of modern molecular biology tools in order to obtain desired phenotypes. However, due to the extreme complexity and interconnectedness of metabolism in all organisms, it is often difficult to a priori predict which changes will yield the optimal results. Flux balance analysis ({FBA}) is a mathematical approach that uses a genomic-scale metabolic network models to afford in silico prediction and optimization of metabolic changes. In particular, a genome-scale approach can help select gene targets for knockout and overexpression. This approach can be used to help expedite the strain engineering process. Here, we give an introduction to the use of {FBA} and provide details for its implementation in a microbial metabolic engineering context. }, added-at = {2018-12-02T16:09:07.000+0100}, address = {New York, NY}, author = {Curran, Kathleen A. and Crook, Nathan C. and Alper, Hal S.}, biburl = {https://www.bibsonomy.org/bibtex/2c93b2950bd22469849ef31de0ff7489a/karthikraman}, chapter = 13, citeulike-article-id = {10234914}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/978-1-61779-483-4\_13}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/22144361}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=22144361}, citeulike-linkout-3 = {http://www.springerlink.com/content/uw868625007rl465}, doi = {10.1007/978-1-61779-483-4\_13}, interhash = {1e9d37b314bdaa571c3d4322d52131c8}, intrahash = {c93b2950bd22469849ef31de0ff7489a}, isbn = {978-1-61779-482-7}, issn = {1940-6029}, journal = {Methods in molecular biology (Clifton, N.J.)}, keywords = {flux-analysis metabolic-engineering}, pages = {197--216}, pmid = {22144361}, posted-at = {2012-07-13 07:00:08}, priority = {2}, publisher = {Springer New York}, series = {Methods in Molecular Biology}, timestamp = {2018-12-02T16:09:07.000+0100}, title = {Using flux balance analysis to guide microbial metabolic engineering.}, url = {http://dx.doi.org/10.1007/978-1-61779-483-4\_13}, volume = 834, year = 2012 }