Evaluating evolutionary multiobjective algorithms for the in silico optimization of mutant strains
In Metabolic Engineering, the identification of genetic manipulations that lead to mutant strains able to produce a given compound of interest is a promising, while still complex process. Evolutionary Algorithms (EAs) have been a successful approach for tackling the underlying in silico optimization...
| Autor principal: | |
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| Outros Autores: | , , |
| Formato: | conferencePaper |
| Idioma: | eng |
| Publicado em: |
2008
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| Assuntos: | |
| Texto completo: | https://hdl.handle.net/1822/16649 |
| País: | Portugal |
| Oai: | oai:repositorium.sdum.uminho.pt:1822/16649 |