Mohd Izzat Yong, Mohd Saberi Mohamad, Yee Wen Choon, Weng Howe Chan, Hasyiya Karimah Adli, Khairul Nizar Syazwan Wsw, Nooraini Yusoff, Muhammad Akmal Remli
{"title":"混合蜜蜂算法和调节开/关最小化优化乳酸和琥珀酸盐生产。","authors":"Mohd Izzat Yong, Mohd Saberi Mohamad, Yee Wen Choon, Weng Howe Chan, Hasyiya Karimah Adli, Khairul Nizar Syazwan Wsw, Nooraini Yusoff, Muhammad Akmal Remli","doi":"10.1515/jib-2022-0003","DOIUrl":null,"url":null,"abstract":"<p><p>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 <i>Escherichia coli</i> as the model organism, the most excellent set of genes in <i>E. coli</i> 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 <i>E. coli</i> by selecting the best set of genes to be removed.</p>","PeriodicalId":53625,"journal":{"name":"Journal of Integrative Bioinformatics","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2022-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9521821/pdf/","citationCount":"0","resultStr":"{\"title\":\"A hybrid of Bees algorithm and regulatory on/off minimization for optimizing lactate and succinate production.\",\"authors\":\"Mohd Izzat Yong, Mohd Saberi Mohamad, Yee Wen Choon, Weng Howe Chan, Hasyiya Karimah Adli, Khairul Nizar Syazwan Wsw, Nooraini Yusoff, Muhammad Akmal Remli\",\"doi\":\"10.1515/jib-2022-0003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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 <i>Escherichia coli</i> as the model organism, the most excellent set of genes in <i>E. coli</i> 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 <i>E. coli</i> by selecting the best set of genes to be removed.</p>\",\"PeriodicalId\":53625,\"journal\":{\"name\":\"Journal of Integrative Bioinformatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2022-07-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9521821/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Integrative Bioinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1515/jib-2022-0003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2022/9/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q3\",\"JCRName\":\"MATHEMATICAL & COMPUTATIONAL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Integrative Bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/jib-2022-0003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/9/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
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 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.