article
Recurrent neural network modeling applied to expanded bed adsorption chromatography of chitosanases produced by Paenibacillus ehimensis
Registro en:
0263-8762
10.1016/j.cherd.2016.09.022
Autor
Souza, Domingos Fabiano de Santana
Padilha, Carlos Eduardo de Araújo
Padilha, Carlos Alberto de Araújo
Oliveira, Jackson Araújo de
Macedo, Gorete Ribeiro de
Santos, Everaldo Silvino dos
Resumen
Nonlinear autoregressive networks with external input (NARX) and multilayer perceptron
(MLP) has been used to predict the activity and protein content for flow-through, washing and elution steps during expanded bed adsorption chromatography of chitosanases
produced by Paenibacillus ehimensis. Bed expansion as well as the influence of particulatecontaining feedstock study showed a stable bed operation without significant impact on
the yield as well as purification factor when the cells were fed to the column. Also, NARXs
showed a better performance to predict the chitosanolytic activity as well as total protein
than MLPs