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...

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Bibliographic Details
Main Author: Maia, Paulo (author)
Other Authors: Rocha, I. (author), Ferreira, Eugénio C. (author), Rocha, Miguel (author)
Format: conferencePaper
Language:eng
Published: 2008
Subjects:
Multiobjective evolutionary algorithms
Metabolic engineering
Flux-balance analysis
Systems biology
Science & Technology
Online Access:https://hdl.handle.net/1822/16649
Country:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/16649

Internet

https://hdl.handle.net/1822/16649

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