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首页> 外文期刊>Journal of Biotechnology >Ensemble optimization of microbial conversion of glycerol into 1, 3-propanediol by Klebsiella pneumoniae
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Ensemble optimization of microbial conversion of glycerol into 1, 3-propanediol by Klebsiella pneumoniae

机译:通过Klebsiella肺炎的甘油的微生物转化为1,3-丙二醇的微生物转化优化

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摘要

Using mathematical model and computer simulation to predict biological processes and optimize the target production is an important strategy for optimizing fermentation process. However, the inherent uncertainty of the kinetic model severely limits the predictive capability. In this study, optimize target production, such as productivity and yield of 1, 3-propanediol produced by Klebsiella pneumoniae using glycerol as substrate, the ensemble modeling approach was used to reduce the model's uncertainty for fermentation process as much as possible, and effectively improve its prediction performance. Firstly, through sensitivity analysis, the parameters having significant influence on the model were determined as the adjustable parameters for the ensemble modeling. After comparison, the appropriate threshold coefficient of the model error was determined, and the sampling method was used to generate as many equivalent parameter sets as possible. Each set of parameters was separately applied for the simulation, and all the predicted values were integrated for the weighted average. Therefore, the expected value of the prediction was obtained. Compared with the traditional simulation using single parameter set, the ensemble modeling method achieved the lower relative error between the prediction and the experimental value and the greatly improved model prediction performance. Moreover, the optimal productivity and yield of 1, 3-propanediol and the corresponding operating conditions were obtained, respectively. The ensemble modeling approach effectively compensates for the uncertainties of the model, making its prediction performance more practical, which is important for computer simulations to predict and guide the actual production process.
机译:使用数学模型和计算机模拟来预测生物过程,优化目标产量是优化发酵过程的重要策略。然而,动力学模型的固有不确定性严重限制了预测能力。在该研究中,优化目标生产,例如使用甘油作为基材的Klebsiella肺炎的1,3-丙二醇的生产率和产率为1,3-丙二醇,用于降低模型对发酵过程的不确定性尽可能多,有效地改善它的预测性能。首先,通过灵敏度分析,确定对模型有显着影响的参数被确定为集合建模的可调参数。比较之后,确定了模型误差的适当阈值系数,并且采样方法用于产生尽可能多的等效参数集。每组参数被单独应用于模拟,并且所有预测值都被整合为加权平均值。因此,获得了预测的预期值。与使用单个参数集的传统模拟相比,集合建模方法实现了预测与实验值之间的相对误差和大大提高的模型预测性能。此外,分别获得了1,3-丙二醇和相应的操作条件的最佳生产率和产率。该集合建模方法有效补偿了模型的不确定性,使其预测性能更加实用,这对于计算机模拟预测和引导实际生产过程很重要。

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