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A hybrid of Bees algorithm and regulatory on/off minimization for optimizing lactate and succinate production

Metabolic engineering has expanded in importance and employment in recent years and is now extensively applied particularly in the production of biomass from microbes. Metabolic network models have been employed extravagantly in computational processes developed to enhance metabolic production and s...

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Detalles Bibliográficos
Autores principales: Yong, Mohd Izzat, Mohamad, Mohd Saberi, Choon, Yee Wen, Chan, Weng Howe, Adli, Hasyiya Karimah, Syazwan WSW, Khairul Nizar, Yusoff, Nooraini, Remli, Muhammad Akmal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: De Gruyter 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9521821/
https://www.ncbi.nlm.nih.gov/pubmed/35852123
http://dx.doi.org/10.1515/jib-2022-0003
Descripción
Sumario:Metabolic engineering has expanded in importance and employment in recent years and is now extensively applied particularly in the production of biomass from microbes. Metabolic network models have been employed extravagantly in computational processes developed to enhance metabolic production and suggest changes in organisms. The crucial issue has been the unrealistic flux distribution presented in prior work on rational modelling framework adopting Optknock and OptGene. In order to address the problem, a hybrid of Bees Algorithm and Regulatory On/Off Minimization (BAROOM) is used. By employing Escherichia coli as the model organism, the most excellent set of genes in E. coli that can be removed and advance the production of succinate can be decided. Evidences shows that BAROOM outperforms alternative strategies used to escalate in succinate production in model organisms like E. coli by selecting the best set of genes to be removed.