[A model for amino acid composition and optimum pH in G/11 xylanase based on neural networks].
In this paper, a prediction model for amino acid composition and optimum pH of xylanase in G/11 family was established in terms of an artificial neural networks based on uniform design. Results showed that the calculated and predicted pHs fitted the optimum pHs of xylanase very well and the MAPEs (Mean mean Absolute Percent Error) were 3.02% and 4.06%, the MSEs (Mean Square Error) were 0.19 and 0.19 pH unit, the MAE (Mean Absolute Error) were 0.11 and 0.19 pH unit, respectively. It was better in fittings and predictions compared with the reported model based on stepwise regression.
Zhang
Guang-Ya
GY
Institute of Industrial Biotechnology, Huaqiao University, Quanzhou 362021, China.
Fang
Bai-Shan
BS
D000596:Amino Acids / Q000737:chemistry*; D006863:Hydrogen-Ion Concentration; D008956:Models, Chemical; D016571:Neural Networks, Computer; D043325:Xylan Endo-1,3-beta-Xylosidase / Q000737:chemistry* / Q000302:isolation & purification
D000596:Amino Acids; D043325:Xylan Endo-1,3-beta-Xylosidase