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Applied Biochemistry and Biotechnology

, Volume 166, Issue 4, pp 997–1007 | Cite as

Exhausted Jackknife Validation Exemplified by Prediction of Temperature Optimum in Enzymatic Reaction of Cellulases

  • Shaomin Yan
  • Guang WuEmail author
Article

Abstract

This was the continuation of our previous study along the same line with more focus on technical details because the data are usually divided into two datasets, one for model development and the other for model validation during the development of predictive model. The widely used validation method is the delete-1 jackknife validation. However, no systematical studies were conducted to determine whether the jackknife validation with different deletions works better because the number of validations with different deletions increases in a factorial fashion. Therefore it is only small dataset that can be used for such an exhausted study. Cellulase is an enzyme playing an important role in modern industry, and many parameters related to cellulase in enzymatic reactions were poorly documented. With increased interests in cellulases in bio-fuel industry, the prediction of parameters in enzymatic reactions is listed on agenda. In this study, two aims were defined (a) which amino acid property works better to predict the temperature optimum and (b) with which deletion the jackknife validation works. The results showed that the amino acid distribution probability works better in predicting the optimum temperature of catalytic reaction by cellulase, and the delete-4, more precisely one-fifth deletion, jackknife validation works better.

Keywords

Cellulase Enzyme Jackknife validation Prediction Temperature optimum 

Notes

Acknowledgments

This study was partly supported by Guangxi Science Foundation (07-109-001-3, 0907016, 10-046-06, 11-031-11, 2010GXNSFF013003, and 2010GXNSFA013046). The authors wish to thank the Library of Guangxi Zhuang Autonomous Region for purchasing the book, Biometry.

Supplementary material

12010_2011_9487_MOESM1_ESM.xls (21 kb)
Supplementary data (XLS 21 kb)

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.State Key Laboratory of Non-food Biomass Enzyme Technology, National Engineering Research Center for Non-food Biorefinery, Guangxi Key Laboratory of BiorefineryGuangxi Academy of SciencesNanningChina
  2. 2.DreamSciTech ConsultingShenzhenChina

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