Conference Proceedings

A Hybrid of Particle Swarm Optimization and Minimization of Metabolic Adjustment for Ethanol Production of Escherichia Coli

Mee K Lee, Mohd Saberi Mohamad, Yee Wen Choon, Kauthar Mohd Daud, Nurul Athirah Nasarudin, Mohd Arfian Ismail, Zuwairie Ibrahim, Suhaimi Napis, Richard O Sinnott, F FdezRiverola (ed.), M Rocha (ed.), MS Mohamad (ed.), N Zaki (ed.), JA CastellanosGarzon (ed.)

PRACTICAL APPLICATIONS OF COMPUTATIONAL BIOLOGY AND BIOINFORMATICS | SPRINGER INTERNATIONAL PUBLISHING AG | Published : 2020

Abstract

Ethanol is a chemical-colourless compound that widely used in pharmaceutical, medicines, food products, and industrial applications. As the demand for ethanol is rising recently, attention has been given on metabolic engineering of Escherichia coli (E.coli) to enhance its production through alteration of its genetic content. This research mainly aimed to optimize ethanol production in E.coli using a gene knockout strategy. Several gene knockout strategies like OptKnock and OptGene have been proposed previously. However, most of them suffer from premature convergence. Hence, a hybrid of Particle Swarm Optimization (PSO) and Minimization of Metabolic Adjustment (MOMA) algorithm is proposed to ..

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Grants

Awarded by Ministry of Education Malaysia


Funding Acknowledgements

We would like to thank the Ministry of Education Malaysia for supporting this research by the Fundamental Research Grant Schemes (grant number: RDU190113 and R.J130000.7828.4F720).