Expression of the Xylanase Gene from Paenibacillus brasilensis X1 in Pichia pastoris and Characteristics of the Recombinant Enzyme

Kalinina, A. N.; Gordeeva, T. L.; Sineoky, S. P.

doi:10.1134/s0003683819080064

Cited by 6 publications

(2 citation statements)

References 32 publications

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“…If the maximum number of iterations is not reached, but the threshold of the objective function is met, terminate the algorithm. (3) If the maximum number of iterations is reached and the threshold of the objective function is met, terminate the algorithm. (4)…”

Section: Icf-pso Algorithm Applied To Optimize the Number And Parameters Of Pwa Local Modelsmentioning

confidence: 99%

“…In addition, the low cost but high yield of the Pichia pastoris expression system makes it economically valuable. Pichia pastoris is also a facultative anaerobe, which is very easy to carry out genetic manipulation and cultivation on [3]. The Pichia pastoris expression system has obvious advantages in the processing, external separation, post-translational modification, and glycosylation modification of expression products [4].…”

Section: Introductionmentioning

confidence: 99%

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Study on Multi-Model Soft Sensor Modeling Method and Its Model Optimization for the Fermentation Process of Pichia pastoris

Wang

et al. 2021

Sensors

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The problems that the key biomass variables in Pichia pastoris fermentation process are difficult measure in real time; this paper mainly proposes a multi-model soft sensor modeling method based on the piecewise affine (PWA) modeling method, which is optimized by particle swarm optimization (PSO) with an improved compression factor (ICF). Firstly, the false nearest neighbor method was used to determine the order of the PWA model. Secondly, the ICF-PSO algorithm was proposed to cooperatively optimize the number of PWA models and the parameters of each local model. Finally, a least squares support vector machine was adopted to determine the scope of action of each local model. Simulation results show that the proposed ICF-PSO-PWA multi-model soft sensor modeling method accurately approximated the nonlinear features of Pichia pastoris fermentation, and the model prediction accuracy is improved by 4.4884% compared with the weighted least squares vector regression model optimized by PSO.

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Section: Icf-pso Algorithm Applied To Optimize the Number And Parameters Of Pwa Local Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Study on Multi-Model Soft Sensor Modeling Method and Its Model Optimization for the Fermentation Process of Pichia pastoris

Wang

et al. 2021

Sensors

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show abstract

Exploring competitive inhibition of a family 10 xylanase derived from Hu sheep rumen microbiota by Oryza sativa xylanase inhibitor protein: In vitro and in silico perspectives

Wang

Liu

et al. 2022

Enzyme and Microbial Technology

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Advances in the understanding of the production, modification and applications of xylanases in the food industry

Mu,

Li,

et al. 2024

Enzyme and Microbial Technology

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Expression of the Xylanase Gene from Paenibacillus brasilensis X1 in Pichia pastoris and Characteristics of the Recombinant Enzyme

Cited by 6 publications

References 32 publications

Study on Multi-Model Soft Sensor Modeling Method and Its Model Optimization for the Fermentation Process of Pichia pastoris

Study on Multi-Model Soft Sensor Modeling Method and Its Model Optimization for the Fermentation Process of Pichia pastoris

Exploring competitive inhibition of a family 10 xylanase derived from Hu sheep rumen microbiota by Oryza sativa xylanase inhibitor protein: In vitro and in silico perspectives

Advances in the understanding of the production, modification and applications of xylanases in the food industry

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