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https://hdl.handle.net/1822/6602
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Campo DC | Valor | Idioma |
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dc.contributor.author | Rocha, Miguel | - |
dc.contributor.author | Pinto, José P. | - |
dc.contributor.author | Rocha, I. | - |
dc.contributor.author | Ferreira, Eugénio C. | - |
dc.date.accessioned | 2007-06-13T20:13:44Z | - |
dc.date.available | 2007-06-13T20:13:44Z | - |
dc.date.issued | 2007-04 | - |
dc.identifier.citation | IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE IN BIOINFORMATICS AND COMPUTATIONAL BIOLOGY, Honolulu, Havai, 2007 – “Proceedings of the 2007 IEEE Symposium on Computacional Intelligence in Bioinformatics and Computational Biology : CIBCB 2007” [CD-ROM]. [S.l.] : IEEE Computational Intelligence Society, 2007. p. 331-337. ISBN 1-4244-0698-6. | eng |
dc.identifier.isbn | 1-4244-0698-6 | - |
dc.identifier.uri | https://hdl.handle.net/1822/6602 | - |
dc.description.abstract | In metabolic engineering it is difficult to identify which set of genetic manipulations will result in a microbial strain that achieves a desired production goal, due to the complexity of the metabolic and regulatory cellular networks and to the lack of appropriate modeling and optimization tools. In this work, Evolutionary Algorithms (EAs) are proposed for the optimization of the set of gene deletions to apply to a microorganism, in order to maximize a given objective function. Each mutant strain is evaluated by resorting to the simulation of its phenotype using the Flux-Balance Analysis approach, together with the premise that microorganisms have maximized their growth along natural evolution. A new set based representation is used in the EAs, using variable size chromosomes, allowing for the automatic discovery of the optimal number of gene deletions. This approach was compared with a traditional binary-based Genetic Algorithm. Two case studies are presented considering the production of succinic and lactic acid as the target, with the bacterium E. coli. The variable size EAs, outperformed the other approaches tested, allowing to reach good results regarding the production of the desired compounds, and additionally presenting low variability among the several runs. | eng |
dc.description.sponsorship | Fundação para a Ciência e a Tecnologia (FCT); FEDER | por |
dc.language.iso | eng | eng |
dc.publisher | IEEE | eng |
dc.relation | info:eu-repo/grantAgreement/FCT/POSC/POSC%2FEIA%2F59899%2F2004/PT | - |
dc.rights | openAccess | eng |
dc.subject | Evolutionary Algorithms | eng |
dc.subject | Set based representations | eng |
dc.subject | Variable size chromosomes | eng |
dc.subject | Metabolic engineering | eng |
dc.subject | Flux-balance analysis | eng |
dc.title | Optimization of bacterial strains with variable-sized evolutionary algorithms | eng |
dc.type | conferencePaper | eng |
dc.peerreviewed | yes | eng |
oaire.citationStartPage | 331 | por |
oaire.citationEndPage | + | por |
dc.subject.wos | Science & Technology | por |
sdum.bookTitle | 2007 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE IN BIOINFORMATICS AND COMPUTATIONAL BIOLOGY | por |
Aparece nas coleções: | CEB - Artigos em Livros de Atas / Papers in Proceedings DI/CCTC - Artigos (papers) |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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CIBCB2007-Hawai_S009P002[2].pdf | 182,21 kB | Adobe PDF | Ver/Abrir |