Partition coefficient prediction of Baker's yeast invertase in aqueous two phase systems using hybrid group method data handling neural network

Carlos Eduardo de Araújo Padilha; Sérgio Dantas de Oliveira Júnior; Domingos Fabiano de Santana Souza; Jackson Araújo de Oliveira; Gorete Ribeiro de Macedo; Everaldo Silvino dos Santos

doi:10.1016/j.cjche.2016.07.015

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Partition coefficient prediction of Baker's yeast invertase in aqueous two phase systems using hybrid group method data handling neural network

Biotechnology and Bioengineering | Updated：2026-01-06

- Partition coefficient prediction of Baker's yeast invertase in aqueous two phase systems using hybrid group method data handling neural network
- Partition coefficient prediction of Baker's yeast invertase in aqueous two phase systems using hybrid group method data handling neural network
- 中国化学工程学报（英文版） 2017年25卷第5期页码：652-657
- Affiliations：
  
  Laboratory of Biochemical Engineering, Chemical Engineering Department, Federal University of Rio Grande do Norte (UFRN), Natal,RN,Brazil
- Author bio：
- Funds：
- DOI：10.1016/j.cjche.2016.07.015
  中图分类号：
- 纸质出版：2017
- Accepted：
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Carlos Eduardo de Araújo Padilha, Sérgio Dantas de Oliveira Júnior, Domingos Fabiano de Santana Souza, 等. Partition coefficient prediction of Baker's yeast invertase in aqueous two phase systems using hybrid group method data handling neural network[J]. 中国化学工程学报（英文版）, 2017,25(5):652-657.

Carlos Eduardo de Araújo Padilha, Sérgio Dantas de Oliveira Júnior, Domingos Fabiano de Santana Souza, Jackson Araújo de Oliveira, Gorete Ribeiro de Macedo, Everaldo Silvino dos Santos. Partition coefficient prediction of Baker's yeast invertase in aqueous two phase systems using hybrid group method data handling neural network[J]. , 2017, 25(5): 652-657.
Carlos Eduardo de Araújo Padilha, Sérgio Dantas de Oliveira Júnior, Domingos Fabiano de Santana Souza, 等. Partition coefficient prediction of Baker's yeast invertase in aqueous two phase systems using hybrid group method data handling neural network[J]. 中国化学工程学报（英文版）, 2017,25(5):652-657. DOI： 10.1016/j.cjche.2016.07.015.

Carlos Eduardo de Araújo Padilha, Sérgio Dantas de Oliveira Júnior, Domingos Fabiano de Santana Souza, Jackson Araújo de Oliveira, Gorete Ribeiro de Macedo, Everaldo Silvino dos Santos. Partition coefficient prediction of Baker's yeast invertase in aqueous two phase systems using hybrid group method data handling neural network[J]. , 2017, 25(5): 652-657. DOI： 10.1016/j.cjche.2016.07.015.

摘要

Abstract

A hybrid GMDH neural network model has been developed in order to predict the partition coefficients of invertase from Baker's yeast. ATPS experiments were carried out changing the molar average mass of PEG (1500-6000 Da)

pH (4.0-7.0)

percentage of PEG (10.0-20.0 w/w)

percentage of MgSO

(8.0-16.0 w/w)

percentage of the cell homogenate (10.0-20.0 w/w) and the percentage of MnSO

(0-5.0 w/w) added as cosolute. The network evaluation was carried out comparing the partition coefficients obtained from the hybrid GMDH neural network with the experimental data using different statistical metrics. The hybrid GMDH neural network model showed better fitting (AARD=32.752%) as well as good generalization capacity of the partition coefficients of the ATPS than the original GMDH network approach and a BPANN model. Therefore hybrid GMDH neural network model appears as a powerful tool for predicting partition coefficients during downstream processing of biomolecules.

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