Parameter Estimation Using Computational Approches in Metabolic Pathways

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Description

The book explains the current issues in bioinformatics approaches to estimate optimal kinetic parameters that can improve the production of desired metabolites. In order to estimate the relevant parameters from data in metabolic pathway, metabolic pathway data was analyzed by using various computational intelligence algorithms. However, many of the computation algorithms face difficulties and take a long computational time to estimate the relevant parameters. The difficulties are due to the existence of noisy data and increasing the number of unknown parameters. Finally, experimental results produce worse search process, less diversity, and less sensitive to control the parameters. The book explains several algorithms with enhanced differential evolution to estimate the optimal kinetic parameters.

Research Ecosystem
Universiti Teknologi Malaysia UTM Nexus - Research & Innovation

Office of Deputy Vice Chancellor (Research & Innovation)

DVCRI Profile Johor Bahru Office Kuala Lumpur Office

Higher Institution Centre of Excellence (HI-COE)

Advance Membrane Technology Research Centre - AMTEC Institute of Noise & Vibration - INV Wireless Communication Centre - WCC

Research Institute

Centre of Excellence (COE)

Institute of High Voltage & High Current - IVAT UTM-MPRC Institue for Oil & Gas - IFOG Centre for Artificial Intelligence & Robotics - CAIRO Centre for Engineering Education - CEE Centre for Advanced Composite Materials - CACM Innovation Centre in Agritechnology for Advanced Bioprocessing - ICA Institute of Bioproduct Development - IBD

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Research Management Centre - RMC Penerbit UTM Press Centre for Community & Industry Network - CCIN Innovation & Commercialisation Centre - ICC University Laboratory Management Centre - PPMU Institut Sultan Iskandar - UTM-ISI

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