Yazar "Balubaid, Mohammed" seçeneğine göre listele

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    MACHINE LEARNING APPLICATION FOR OPTIMIZING ASYMMETRICAL REDUCTION OF ACETOPHENONE EMPLOYING COMPLETE CELL OF LACTOBACILLUS SENMAIZUKE AS AN ENVIRONMENTALLY FRIENDLY APPROACH
    (Health & Environment Assoc, 2020) Taylan, Osman; Yilmaz, Mustafa Tahsin; Balubaid, Mohammed; Alamoudi, Rami; El-Obeid, Tahra; Dertli, Enes; Sahin, Engin
    Recently, optimization of the bioreduction reactions by optimization methodologies has gained special interest as these reactions are affected by several extrinsic factors that should be optimized for higher yields. An important example for these kinds of reactions is the complete cell implications for the bioreduction of prochiral ketones in which the culture parameters play crucial roles. Such biocatalysts provide environmentally friendly and clean methodology to perform reactions under mild conditions with high conversion rates. In the present work, at the first step the Lactobacillus senmaizuke was isolated from sourdough and the complete cell application of Lactobacillus senmaizuke for the bioreduction of acetophenone was optimized by an Artificial Neural networks (ANNs) to achieve the highest enantiomeric excess (EE, %). The culture parameters, pH, temperature, incubation period and agitation speed were the experimental factors that were optimized to maximize EE (%) by machine learning algorithm of Artificial Intelligence modeling and the best conditions to maximize EE (95.5 %) were calculated to be pH of 5.7, temperature of 35 degrees C, incubation period of 76 h and agitation speed of 240 rpm with very low sum of squared error value (0.611236 %) to bioreduce acetophenone using complete cell of Lactobacillus senmaizuke as a sourdough isolate GRAS microbial species. Accordingly, The ANN was employed to correctly establish the enantiomeric excess values of the specimen with an average absolute error 0.080739 %.
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    Optimization of lactose derivative hetero-oligosaccharides production using whey as the acceptor molecule by an active glucansucrase
    (Taylor & Francis Ltd, 2022) Kabli, Mohammad; Ispirli, Humeyra; Balubaid, Mohammed; Taylan, Osman; Yilmaz, Mustafa Tahsin; Dertli, Enes
    Glucansucrases are capable of synthesis of distinct oligosaccharides using different acceptor molecules and in this study lactose derivative hetero-oligosaccharides were shown to be produced by an active glucansucrase in its acceptor reaction with sucrose and whey as the donor-acceptor molecules, respectively. Following the monitoring of the reaction products by TLC analysis, the effects of reaction parameters in terms of enzyme concentration, sucrose/whey ratio and reaction temperature on final oligosaccharide yields (OY) were optimized by Response Surface Methodology (RSM). Results indicated that increment of enzyme concentration and reaction temperature decreased the OY in a particular reaction time whereas the OY increased with the increment of sucrose/whey ratio in the acceptor reactions of glucansucrase E81 with whey as the acceptor molecule. A low level of glucansucrase E81 concentration was sufficient to obtain the highest OY in the tested conditions. These findings demonstrated the importance of the optimisation of the reaction parameters for the acceptor reactions of the glucansucrases.