Global optimization applied to kinetic models of metabolic networks
In recent years, the use of genetic manipulation techniques has opened the door for obtaining microorganisms with enhanced phenotypes, which has in turn led to significant improvements in the synthesis of certain biochemical products. However, mutation and selection of these new organisms has been p...
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| Tipo de recurso: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2012 |
| País: | España |
| Institución: | Universitat Rovira i virgili (URV) |
| Repositorio: | Repositori Institucional de la Universitat Rovira i Virgili |
| OAI Identifier: | oai:urv.cat:TDX:1137 |
| Acceso en línea: | https://hdl.handle.net/20.500.11797/TDX1137 http://hdl.handle.net/10803/96660 |
| Access Level: | acceso abierto |
| Palabra clave: | 66 - Enginyeria, tecnologia i indústria química. Metal·lúrgia 57 - Biologia 51 - Matemàtiques |
| Sumario: | In recent years, the use of genetic manipulation techniques has opened the door for obtaining microorganisms with enhanced phenotypes, which has in turn led to significant improvements in the synthesis of certain biochemical products. However, mutation and selection of these new organisms has been performed, in most cases, in a trial-and-error basis. It is expected that these processes could be further improved if quantitative design principles were used to guide the search towards the ideal enzymatic profiles. This thesis is devoted to developing a set of advanced global optimization tools to assess metabolic engineering problems and other questions arising in systems biology. In particular, we focus on problems where metabolic networks are modeled making use of kinetic expressions. The usefulness of the algorithms developed to solve such problems is demonstrated by means of several case studies. |
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