Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/3134
Title: A Hybrid of Bees Algorithm and Regulatory On/Off Minimization for Optimizing Lactate Production
Authors: Yong, Mohd Izzata 
Mohamad, Mohd Saberi 
Choon, Yee Wen 
Chan, Weng Howe 
Adli, H.K. 
Syazwan K.N. 
Yusoff, Nooraini 
Remli, Muhammad Akmal 
Keywords: Artificial Intelligence;Bioinformatics;Gene knockout;Metabolic engineering;Modelling;Optgene;Optimization;OptKnock
Issue Date: 2022
Publisher: Springer Science and Business Media Deutschland GmbH
Journal: Lecture Notes in Networks and Systems 
Conference: 15th International Conference on Practical Applications of Computational Biology and Bioinformatics, PACBB 2021 
Abstract: 
Metabolic engineering has grown dramatically and is now widely used, particularly in the production of biomass utilising microorganisms. The metabolic network model has been extensively used in computational procedures developed to optimise metabolic production and suggest modifications in organisms. The problem has been the unrealistic flux distribution suggestion demonstrated by previous work on a rational modelling framework employing Optknock and OptGene. To address the issue, a hybrid of the Bees Algorithm and Regulatory On/Off Minimization (BAROOM) is introduced. By using Eschericia coli (E. coli) as the model organism, BAROOM is able to determine the optimal set of gene that can be knocked out and improve lactate production. The results show that BAROOM performs better than other methods in increasing lactate production in model organism by identifying optimal set of genes to be knocked out.
Description: 
Scopus
URI: http://hdl.handle.net/123456789/3134
ISBN: 978-303086257-2
ISSN: 23673370
DOI: 10.1007/978-3-030-86258-9_10
Appears in Collections:Faculty of Data Science and Computing - Proceedings

Show full item record

Google ScholarTM

Check

Altmetric

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.