换一批Medium optimization for pyrroloquinoline quinone (PQQ) production by Methylobacillus sp. zju323 using response surface methodology and artificial neural network-genetic algorithm.
第一作者：
Peilian,Wei
第一单位：
a School of Biological and Chemical Engineering, Zhejiang University of Science & Technology , Hangzhou , P. R. China.
作者：
关键词
AAD, average absolute deviationANN, artificial neural networkANOVA, analysis of varianceAOMM, ANN-optimized methanol mediumAdj R2, adjusted coefficient of determinationArtificial neural networkBP, back propagationC.V., coefficient of variationCCD, central composite designDO, dissolved oxygenGA, genetic algorithmLM, Levenberg–MarquardtMLP, multilayered perceptronOMM, original methanol mediumPABA, ρ-amino benzoic acidPBD, Plackett–Burman designPQQ, pyrroloquinoline quinonePred R2, predicted coefficient of determinationR2, coefficient of determinationRMSE, root mean square errorRP, resilient back propagationRSM, response surface methodologySA, steepest ascentSCG, scaled conjugate gradientfermentationgenetic algorithmpyrroloquinoline quinoneresponse surface methodology
医学主题词
算法(Algorithms);培养基(Culture Media);发酵(Fermentation);工业微生物学(Industrial Microbiology);甲基芽孢杆菌属(Methylobacillus);PQQ辅因子(PQQ Cofactor)
DOI
10.1080/10826068.2017.1315596
PMID
28448745
发布时间
2019-12-10
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