Identifying gene knockout strategies using a hybrid of bees algorithm and flux balance analysis for in silico optimization of microbial strains
Genome-scale metabolic networks reconstructions from different organisms have become popular in recent years. Genetic engineering is proven to be able to obtain the desirable phenotypes. Optimization algorithms are implemented in previous works to identify the effects of gene knockout on the results...
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my.utm.358062017-02-04T06:43:20Z http://eprints.utm.my/id/eprint/35806/ Identifying gene knockout strategies using a hybrid of bees algorithm and flux balance analysis for in silico optimization of microbial strains Yee, Wen Choon Mohammad, Mohd. Saberi Deris, Safaai Chuii, Khim Chong Lian, En Chai Ibrahim, Zuwairie Omatu, Sigeru QA75 Electronic computers. Computer science Genome-scale metabolic networks reconstructions from different organisms have become popular in recent years. Genetic engineering is proven to be able to obtain the desirable phenotypes. Optimization algorithms are implemented in previous works to identify the effects of gene knockout on the results. However, the previous works face the problem of falling into local minima. Thus, a hybrid of Bees Algorithm and Flux Balance Analysis (BAFBA) is proposed in this paper to solve the local minima problem and to predict optimal sets of gene deletion for maximizing the growth rate of certain metabolite. This paper involves two case studies that consider the production of succinate and lactate as targets, by using E.coli as model organism. The results from this experiment are the list of knockout genes and the growth rate after the deletion. BAFBA shows better results compared to the other methods. The identified list suggests gene modifications over several pathways and may be useful in solving challenging genetic engineering problems. Springer-Verlag. 2012 Book Section PeerReviewed Yee, Wen Choon and Mohammad, Mohd. Saberi and Deris, Safaai and Chuii, Khim Chong and Lian, En Chai and Ibrahim, Zuwairie and Omatu, Sigeru (2012) Identifying gene knockout strategies using a hybrid of bees algorithm and flux balance analysis for in silico optimization of microbial strains. In: Advances in Intelligent and Soft Computing. Springer-Verlag., Berlin, pp. 371-378. ISBN 978-364228764-0 http://dx.doi.org/10.1007/978-3-642-28765-7_44 DOI:10.1007/978-3-642-28765-7_44 |
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QA75 Electronic computers. Computer science Yee, Wen Choon Mohammad, Mohd. Saberi Deris, Safaai Chuii, Khim Chong Lian, En Chai Ibrahim, Zuwairie Omatu, Sigeru Identifying gene knockout strategies using a hybrid of bees algorithm and flux balance analysis for in silico optimization of microbial strains |
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Genome-scale metabolic networks reconstructions from different organisms have become popular in recent years. Genetic engineering is proven to be able to obtain the desirable phenotypes. Optimization algorithms are implemented in previous works to identify the effects of gene knockout on the results. However, the previous works face the problem of falling into local minima. Thus, a hybrid of Bees Algorithm and Flux Balance Analysis (BAFBA) is proposed in this paper to solve the local minima problem and to predict optimal sets of gene deletion for maximizing the growth rate of certain metabolite. This paper involves two case studies that consider the production of succinate and lactate as targets, by using E.coli as model organism. The results from this experiment are the list of knockout genes and the growth rate after the deletion. BAFBA shows better results compared to the other methods. The identified list suggests gene modifications over several pathways and may be useful in solving challenging genetic engineering problems. |
format |
Book Section |
author |
Yee, Wen Choon Mohammad, Mohd. Saberi Deris, Safaai Chuii, Khim Chong Lian, En Chai Ibrahim, Zuwairie Omatu, Sigeru |
author_facet |
Yee, Wen Choon Mohammad, Mohd. Saberi Deris, Safaai Chuii, Khim Chong Lian, En Chai Ibrahim, Zuwairie Omatu, Sigeru |
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Yee, Wen Choon |
title |
Identifying gene knockout strategies using a hybrid of bees algorithm and flux balance analysis for in silico optimization of microbial strains |
title_short |
Identifying gene knockout strategies using a hybrid of bees algorithm and flux balance analysis for in silico optimization of microbial strains |
title_full |
Identifying gene knockout strategies using a hybrid of bees algorithm and flux balance analysis for in silico optimization of microbial strains |
title_fullStr |
Identifying gene knockout strategies using a hybrid of bees algorithm and flux balance analysis for in silico optimization of microbial strains |
title_full_unstemmed |
Identifying gene knockout strategies using a hybrid of bees algorithm and flux balance analysis for in silico optimization of microbial strains |
title_sort |
identifying gene knockout strategies using a hybrid of bees algorithm and flux balance analysis for in silico optimization of microbial strains |
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Springer-Verlag. |
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2012 |
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http://eprints.utm.my/id/eprint/35806/ http://dx.doi.org/10.1007/978-3-642-28765-7_44 |
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1643649846071001088 |
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13.15806 |