Identifying a Gene Knockout Strategy Using a Hybrid of Simple Constrained Artificial Bee Colony Algorithm and Flux Balance Analysis to Enhance the Production of Succinate and Lactate in Escherichia Coli-Reference-Cited by-同舟云学术

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Identifying a Gene Knockout Strategy Using a Hybrid of Simple Constrained Artificial Bee Colony Algorithm and Flux Balance Analysis to Enhance the Production of Succinate and Lactate in Escherichia Coli

Published:2019-02-13 Issue:1 Volume:11 Page:33-44
ISSN:1913-2751
Container-title:Interdisciplinary Sciences: Computational Life Sciences
language:en
Short-container-title:Interdiscip Sci Comput Life Sci

Author:

Hon Mei Kie,Mohamad Mohd Saberi,Mohamed Salleh Abdul Hakim,Choon Yee Wen,Mohd Daud Kauthar,Remli Muhammad Akmal,Ismail Mohd Arfian,Omatu Sigeru,Sinnott Richard O.,Corchado Juan Manuel

Funder

Ministry of Higher Education, Malaysia

Universiti Teknologi Malaysia

Universiti Malaysia Pahang

Publisher

Springer Science and Business Media LLC

Subject

Health Informatics,Computer Science Applications,General Biochemistry, Genetics and Molecular Biology

Link

http://link.springer.com/article/10.1007/s12539-019-00324-z/fulltext.html

Reference23 articles.

1. Lee SJ, Lee DY, Kim TY, Kim BH, Lee J, Lee SY (2005) Metabolic engineering of escherichia coli for enhanced production of succinic acid, based on genome comparison and in silico gene knockout simulation. Appl Environ Microbiol 71:7880. https://doi.org/10.1128/AEM.71.12.7880-7887.2005

2. Burgard AP, Pharkya P, Maranas CD (2003) Optknock: a bilevel programming framework for identifying gene knockout strategies for microbial strain optimization. Biotechnol Bioeng 84(6):647–657. https://doi.org/10.1002/bit.10803

3. Patil KR, Rocha I, Forster J, Nielsen J (2005) Evolutionary programming as a platform for in silico metabolic engineering. BMC Bioinform 6(1):1–12. https://doi.org/10.1186/14702105-6-308

4. Rocha M, Maia P, Mendes R, Pinto JP, Ferreira EC, Nielsen J, Patil KR, Rocha I (2008) Natural computation meta-heuristics for the in silico optimization of microbial strains. BMC Bioinform 9:499. https://doi.org/10.1186/1471-2105-9-499

5. Martino GD, Cardillo FA, Starita A (2006) A new swarm intelligence coordination model inspired by collective prey retrieval and its application to image alignment. In: Runarsson T, Beyer HG, Burke E, Merelo-Guervós J, Whitley LD, Yao X (eds) Parallel problem solving from Nature—PPSN IX Springer, Berlin, pp 691–700

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