In silico metabolites production enhancement using hybrid genetic colony optimization and flux balance analysis

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Main Author: Abdul Hakim Mohamed Salleh
Format: Thesis
Published: 2014
Subjects:
Online Access:http://eprints.utm.my/id/eprint/48481/
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Institution: Universiti Teknologi Malaysia
id my.utm.48481
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spelling my.utm.484812015-10-15T01:09:09Z http://eprints.utm.my/id/eprint/48481/ In silico metabolites production enhancement using hybrid genetic colony optimization and flux balance analysis Abdul Hakim Mohamed Salleh, QH Natural history 2014 Thesis NonPeerReviewed Abdul Hakim Mohamed Salleh, (2014) In silico metabolites production enhancement using hybrid genetic colony optimization and flux balance analysis. Masters thesis, Universiti Teknologi Malaysia, Faculty of Computing.
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QH Natural history
spellingShingle QH Natural history
Abdul Hakim Mohamed Salleh,
In silico metabolites production enhancement using hybrid genetic colony optimization and flux balance analysis
format Thesis
author Abdul Hakim Mohamed Salleh,
author_facet Abdul Hakim Mohamed Salleh,
author_sort Abdul Hakim Mohamed Salleh,
title In silico metabolites production enhancement using hybrid genetic colony optimization and flux balance analysis
title_short In silico metabolites production enhancement using hybrid genetic colony optimization and flux balance analysis
title_full In silico metabolites production enhancement using hybrid genetic colony optimization and flux balance analysis
title_fullStr In silico metabolites production enhancement using hybrid genetic colony optimization and flux balance analysis
title_full_unstemmed In silico metabolites production enhancement using hybrid genetic colony optimization and flux balance analysis
title_sort in silico metabolites production enhancement using hybrid genetic colony optimization and flux balance analysis
publishDate 2014
url http://eprints.utm.my/id/eprint/48481/
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