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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 |
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