{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T01:02:16Z","timestamp":1774400536382,"version":"3.50.1"},"reference-count":18,"publisher":"Walter de Gruyter GmbH","issue":"3","license":[{"start":{"date-parts":[[2022,7,19]],"date-time":"2022-07-19T00:00:00Z","timestamp":1658188800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100004693","name":"Universiti Malaysia Kelantan","doi-asserted-by":"publisher","award":["R\/FUND\/A0100\/01850A\/001\/2020\/00816"],"award-info":[{"award-number":["R\/FUND\/A0100\/01850A\/001\/2020\/00816"]}],"id":[{"id":"10.13039\/501100004693","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100015515","name":"Kementerian Pendidikan Malaysia","doi-asserted-by":"publisher","award":["R\/FRGS\/A0800\/01655A\/003\/2020\/00720"],"award-info":[{"award-number":["R\/FRGS\/A0800\/01655A\/003\/2020\/00720"]}],"id":[{"id":"10.13039\/501100015515","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,9,30]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats: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 <jats:italic>Escherichia coli<\/jats:italic> as the model organism, the most excellent set of genes in <jats:italic>E. coli<\/jats:italic> 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 <jats:italic>E. coli<\/jats:italic> by selecting the best set of genes to be removed.<\/jats:p>","DOI":"10.1515\/jib-2022-0003","type":"journal-article","created":{"date-parts":[[2022,7,19]],"date-time":"2022-07-19T04:20:03Z","timestamp":1658204403000},"source":"Crossref","is-referenced-by-count":2,"title":["A hybrid of Bees algorithm and regulatory on\/off minimization for optimizing lactate and succinate production"],"prefix":"10.1515","volume":"19","author":[{"given":"Mohd Izzat","family":"Yong","sequence":"first","affiliation":[{"name":"Artificial Intelligence and Bioinformatics Research Group, Faculty of Computing , Universiti Teknologi Malaysia , 81310 Johor , Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohd Saberi","family":"Mohamad","sequence":"additional","affiliation":[{"name":"Health Data Science Lab Department of Genetics and Genomics,College of Medical and Health Sciences , United Arab Emirates University , P.O. Box 17666, Al Ain , Abu Dhabi , United Arab Emirates"},{"name":"Big Data Analytics Center , United Arab Emirates University , Al Ain , Abu Dhabi , United Arab Emirates"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yee Wen","family":"Choon","sequence":"additional","affiliation":[{"name":"Institute for Artificial Intelligence and Big Data , Universiti Malaysia Kelantan , Kota Bharu , 16100 , Kelantan , Malaysia"},{"name":"Department of Data Science , Universiti Malaysia Kelantan , City Campus, Pengkalan Chepa , 16100 Kota Bharu , Kelantan, Malaysia ,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weng Howe","family":"Chan","sequence":"additional","affiliation":[{"name":"Artificial Intelligence and Bioinformatics Research Group, Faculty of Computing , Universiti Teknologi Malaysia , 81310 Johor , Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hasyiya Karimah","family":"Adli","sequence":"additional","affiliation":[{"name":"Institute for Artificial Intelligence and Big Data , Universiti Malaysia Kelantan , Kota Bharu , 16100 , Kelantan , Malaysia"},{"name":"Department of Data Science , Universiti Malaysia Kelantan , City Campus, Pengkalan Chepa , 16100 Kota Bharu , Kelantan, Malaysia ,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Khairul Nizar","family":"Syazwan WSW","sequence":"additional","affiliation":[{"name":"Institute for Artificial Intelligence and Big Data , Universiti Malaysia Kelantan , Kota Bharu , 16100 , Kelantan , Malaysia"},{"name":"Department of Data Science , Universiti Malaysia Kelantan , City Campus, Pengkalan Chepa , 16100 Kota Bharu , Kelantan, Malaysia ,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nooraini","family":"Yusoff","sequence":"additional","affiliation":[{"name":"Institute for Artificial Intelligence and Big Data , Universiti Malaysia Kelantan , Kota Bharu , 16100 , Kelantan , Malaysia"},{"name":"Department of Data Science , Universiti Malaysia Kelantan , City Campus, Pengkalan Chepa , 16100 Kota Bharu , Kelantan, Malaysia ,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Muhammad Akmal","family":"Remli","sequence":"additional","affiliation":[{"name":"Institute for Artificial Intelligence and Big Data , Universiti Malaysia Kelantan , Kota Bharu , 16100 , Kelantan , Malaysia"},{"name":"Department of Data Science , Universiti Malaysia Kelantan , City Campus, Pengkalan Chepa , 16100 Kota Bharu , Kelantan, Malaysia ,"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"374","published-online":{"date-parts":[[2022,7,19]]},"reference":[{"key":"2023033120301378220_j_jib-2022-0003_ref_001","doi-asserted-by":"crossref","unstructured":"Baba, T, Ara, T, Hasegawa, M, Takai, Y, Okumura, Y, Baba, M, et al.. Construction of Escherichia coli K-12 in-frame, single-gene knockout mutants: Keio collection. Mol Syst Biol 2006;2:1\u201311. https:\/\/doi.org\/10.1038\/msb4100050.","DOI":"10.1038\/msb4100050"},{"key":"2023033120301378220_j_jib-2022-0003_ref_002","doi-asserted-by":"crossref","unstructured":"Pham, DT, Ghanbarzadeh, A, Ko\u00e7, E, Otri, S, Rahim, S, Zaidi, M. The bees algorithm\u2014a novel tool for complex optimisation problems. In: Intelligent production machines and systems. Elsevier Science Ltd; 2006:454\u20139\u00a0pp.","DOI":"10.1016\/B978-008045157-2\/50081-X"},{"key":"2023033120301378220_j_jib-2022-0003_ref_003","doi-asserted-by":"crossref","unstructured":"Choon, YW, Mohamad, MS, Deris, S, Chong, CK, Chai, LE, Ibrahim, Z, et al.. Identifying gene knockout strategies using a hybrid of bees algorithm and flux balance analysis for in silico optimization of microbial strains. In: Distributed computing and artificial intelligence. Berlin, Heidelberg: Springer; 2012:371\u20138\u00a0pp.","DOI":"10.1007\/978-3-642-28765-7_44"},{"key":"2023033120301378220_j_jib-2022-0003_ref_004","doi-asserted-by":"crossref","unstructured":"Choon, YW, Mohamad, MS, Deris, S, Chong, CK, Omatu, S, Corchado, JM. Gene knockout identification using an extension of bees hill flux balance analysis. BioMed research international; 2015.","DOI":"10.1155\/2015\/124537"},{"key":"2023033120301378220_j_jib-2022-0003_ref_005","doi-asserted-by":"crossref","unstructured":"Kleessen, S, Nikoloski, Z. Dynamic regulatory on\/off minimization for biological systems under internal temporal perturbations. BMC Syst Biol 2012;6:16. https:\/\/doi.org\/10.1186\/1752-0509-6-16.","DOI":"10.1186\/1752-0509-6-16"},{"key":"2023033120301378220_j_jib-2022-0003_ref_006","doi-asserted-by":"crossref","unstructured":"Shlomi, T, Berkman, O, Ruppin, E. Regulatory on-off minimization of metabolic flux changes after genetic perturbations. Proc Natl Acad Sci USA 2005;102:7695\u2013700. https:\/\/doi.org\/10.1073\/pnas.0406346102.","DOI":"10.1073\/pnas.0406346102"},{"key":"2023033120301378220_j_jib-2022-0003_ref_007","doi-asserted-by":"crossref","unstructured":"Burgard, AP, Pharkya, P, Maranas, CD. OptKnock: a bilevel programming framework for identifying gene knockout strategies for microbial strain optimization. Biotechnol Bioeng 2003;84:647\u201357. https:\/\/doi.org\/10.1002\/bit.10803.","DOI":"10.1002\/bit.10803"},{"key":"2023033120301378220_j_jib-2022-0003_ref_008","doi-asserted-by":"crossref","unstructured":"Feist, AM, Zielinski, DC, Orth, JD, Schellenberger, J, Herrgard, MJ, Palsson, B. Model-driven evaluation of the production potential for growth coupled products of Escherichia coli. Metab Eng 2010;12:173\u201386. https:\/\/doi.org\/10.1016\/j.ymben.2009.10.003.","DOI":"10.1016\/j.ymben.2009.10.003"},{"key":"2023033120301378220_j_jib-2022-0003_ref_009","doi-asserted-by":"crossref","unstructured":"Yanase, H, Sato, D, Yamamoto, K, Matsuda, S, Yamamoto, S, Okamoto, K. Genetic engineering of zymobacter palmae for production of ethanol from xylose. Appl Environ Microbiol 2007;73:2592\u20139. https:\/\/doi.org\/10.1128\/aem.02302-06.","DOI":"10.1128\/AEM.02302-06"},{"key":"2023033120301378220_j_jib-2022-0003_ref_010","doi-asserted-by":"crossref","unstructured":"Cheng, K, Wang, G, Zeng, J, Zhang, J. Improved succinate production by metabolic engineering. BioMed Res Int 2013;2013:1\u201312. https:\/\/doi.org\/10.1155\/2013\/538790.","DOI":"10.1155\/2013\/538790"},{"key":"2023033120301378220_j_jib-2022-0003_ref_011","doi-asserted-by":"crossref","unstructured":"Terzer, M, Maynard, ND, Covert, MW, Stelling, J. Genome scale metabolic networks. System Biology and Medicine 2009;1:285\u201397. https:\/\/doi.org\/10.1002\/wsbm.37.","DOI":"10.1002\/wsbm.37"},{"key":"2023033120301378220_j_jib-2022-0003_ref_012","doi-asserted-by":"crossref","unstructured":"Zhao, J, Baba, T, Mori, H, Shimizu, K. Effect of zwf gene knockout on the metabolism of Escherichia coli grown on glucose or acetate. Metab Eng 2004;6:164\u201374. https:\/\/doi.org\/10.1016\/j.ymben.2004.02.004.","DOI":"10.1016\/j.ymben.2004.02.004"},{"key":"2023033120301378220_j_jib-2022-0003_ref_013","doi-asserted-by":"crossref","unstructured":"Park, S, Cotter, P, Gunsalus, RP. Regulation of malate dehydrogenase (mdh) gene expression in Escherichia coli in response to oxygen, carbon, and heme availability. J Bacteriol 1995;177:6652\u20136. https:\/\/doi.org\/10.1128\/jb.177.22.6652-6656.1995.","DOI":"10.1128\/jb.177.22.6652-6656.1995"},{"key":"2023033120301378220_j_jib-2022-0003_ref_014","doi-asserted-by":"crossref","unstructured":"Ren, S, Zeng, B, Qian, X. Adaptive Bi-level programming for optimal gene knockouts for targeted overproduction under phenotypic constraints. BMC Bioinf 2013;14:1\u201311. https:\/\/doi.org\/10.1186\/1471-2105-14-s2-s17.","DOI":"10.1186\/1471-2105-14-S2-S17"},{"key":"2023033120301378220_j_jib-2022-0003_ref_015","doi-asserted-by":"crossref","unstructured":"Yang, Y, Benett, GN, San, K. Effect of inactivation of nuo and ackA-pta on redistribution of metabolic fluxes in Escherichia coli. Biotechnol Bioeng 1999;65:291\u20137. https:\/\/doi.org\/10.1002\/(sici)1097-0290(19991105)65:3<291::aid-bit6>3.0.co;2-f.","DOI":"10.1002\/(SICI)1097-0290(19991105)65:3<291::AID-BIT6>3.0.CO;2-F"},{"key":"2023033120301378220_j_jib-2022-0003_ref_016","doi-asserted-by":"crossref","unstructured":"Zhu, J, Shimizu, K. Effect of a single-gene knockout on the metabolic regulation in Escherichia coli for D-lactate production under microaerobic condition. Metab Eng 2005;7:104\u201315. https:\/\/doi.org\/10.1016\/j.ymben.2004.10.004.","DOI":"10.1016\/j.ymben.2004.10.004"},{"key":"2023033120301378220_j_jib-2022-0003_ref_017","unstructured":"Jantama, K. Glucose is taken up by galactose permease in metabolic engineered Escherichia coli to produce succinate. Suranaree J Sci Technol 2010;17:369\u201386."},{"key":"2023033120301378220_j_jib-2022-0003_ref_018","doi-asserted-by":"crossref","unstructured":"Yoo, M, Soucaille, P. Trends in systems biology for the analysis and engineering of Clostridium acetobutylicum metabolism. Trends Microbiol 2020;28:118\u201340. https:\/\/doi.org\/10.1016\/j.tim.2019.09.003.","DOI":"10.1016\/j.tim.2019.09.003"}],"container-title":["Journal of Integrative Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/jib-2022-0003\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/jib-2022-0003\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,1]],"date-time":"2023-04-01T09:53:52Z","timestamp":1680342832000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/jib-2022-0003\/html"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,19]]},"references-count":18,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2022,4,8]]},"published-print":{"date-parts":[[2022,9,30]]}},"alternative-id":["10.1515\/jib-2022-0003"],"URL":"https:\/\/doi.org\/10.1515\/jib-2022-0003","relation":{},"ISSN":["1613-4516"],"issn-type":[{"value":"1613-4516","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,7,19]]},"article-number":"20220003"}}