{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,19]],"date-time":"2024-08-19T09:04:58Z","timestamp":1724058298455},"reference-count":17,"publisher":"Walter de Gruyter GmbH","issue":"2","license":[{"start":{"date-parts":[[2023,6,1]],"date-time":"2023-06-01T00:00:00Z","timestamp":1685577600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100006013","name":"United Arab Emirates University","doi-asserted-by":"publisher","award":["Vot: 12M109"],"id":[{"id":"10.13039\/501100006013","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,7,31]]},"abstract":"Abstract<\/jats:title>\n Analyzing metabolic pathways in systems biology requires accurate kinetic parameters that represent the simulated in vivo<\/jats:italic> processes. Simulation of the fermentation pathway in the Saccharomyces cerevisiae<\/jats:italic> kinetic model help saves much time in the optimization process. Fitting the simulated model into the experimental data is categorized under the parameter estimation problem. Parameter estimation is conducted to obtain the optimal values for parameters related to the fermentation process. This step is essential because insufficient identification of model parameters can cause erroneous conclusions. The kinetic parameters cannot be measured directly. Therefore, they must be estimated from the experimental data either in vitro<\/jats:italic> or in vivo<\/jats:italic>. Parameter estimation is a challenging task in the biological process due to the complexity and nonlinearity of the model. Therefore, we propose the Artificial Bee Colony algorithm (ABC) to estimate the parameters in the fermentation pathway of S. cerevisiae<\/jats:italic> to obtain more accurate values. A metabolite with a total of six parameters is involved in this article. The experimental results show that ABC outperforms other estimation algorithms and gives more accurate kinetic parameter values for the simulated model. Most of the estimated kinetic parameter values obtained from the proposed algorithm are the closest to the experimental data.<\/jats:p>","DOI":"10.1515\/jib-2022-0051","type":"journal-article","created":{"date-parts":[[2023,6,21]],"date-time":"2023-06-21T13:11:15Z","timestamp":1687353075000},"source":"Crossref","is-referenced-by-count":1,"title":["Artificial Bee Colony algorithm in estimating kinetic parameters for yeast fermentation pathway"],"prefix":"10.1515","volume":"20","author":[{"given":"Ahmad Muhaimin","family":"Ismail","sequence":"first","affiliation":[{"name":"Artificial Intelligence and Bioinformatics Research Group, Faculty of Computing , Universiti Teknologi Malaysia , 81310 Skudai , Johor , Malaysia"}]},{"given":"Muhammad Akmal","family":"Remli","sequence":"additional","affiliation":[{"name":"Institute for Artificial Intelligence and Big Data, Universiti Malaysia Kelantan , 16100 Kota Bharu , Kelantan , Malaysia"},{"name":"Faculty of Data Science and Computing , Universiti Malaysia Kelantan , 16100 Kota Bharu , Kelantan , Malaysia"}]},{"given":"Yee Wen","family":"Choon","sequence":"additional","affiliation":[{"name":"Institute for Artificial Intelligence and Big Data, Universiti Malaysia Kelantan , 16100 Kota Bharu , Kelantan , Malaysia"},{"name":"Faculty of Data Science and Computing , Universiti Malaysia Kelantan , 16100 Kota Bharu , Kelantan , Malaysia"}]},{"given":"Nurul Athirah","family":"Nasarudin","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 15551 , Al Ain , United Arab Emirates"}]},{"given":"Nor-Syahidatul N.","family":"Ismail","sequence":"additional","affiliation":[{"name":"Faculty of Computing, College of Computing & Applied Sciences , Universiti Malaysia Pahang , 26300 Gambang , Pahang , Malaysia"}]},{"given":"Mohd Arfian","family":"Ismail","sequence":"additional","affiliation":[{"name":"Faculty of Computing, College of Computing & Applied Sciences , Universiti Malaysia Pahang , 26300 Gambang , Pahang , Malaysia"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-1079-4559","authenticated-orcid":false,"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 15551 , Al Ain , United Arab Emirates"}]}],"member":"374","published-online":{"date-parts":[[2023,6,22]]},"reference":[{"key":"2023073113214250312_j_jib-2022-0051_ref_001","doi-asserted-by":"crossref","unstructured":"Chou, IC, Voit, EO. Recent developments in parameter estimation and structure identification of biochemical and genomic systems. Math Biosci 2009;219:57\u201383. https:\/\/doi.org\/10.1016\/j.mbs.2009.03.002.","DOI":"10.1016\/j.mbs.2009.03.002"},{"key":"2023073113214250312_j_jib-2022-0051_ref_002","doi-asserted-by":"crossref","unstructured":"Curto, R, Sorribas, A, Cascante, M. Comparative characterization of the fermentation pathway of Saccharomyces cerevisiae using biochemical systems theory and metabolic control analysis: model definition and nomenclature. 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