Predicting the temperature of thermostable proteins based on hurst exponent and choquet integral

Hsiang Chuan Liu, Wei Sung Chen, Shang Ling Ou, Yih Chang Ou, Hsien Chang Tsai, Jing Ming Ju

Research output: Contribution to journalArticle

Abstract

In this paper, for predicting the temperature of thermostable proteins on some useful physicochemical quantities of each amino symbolic sequence with different lengths, a novel integrated algorithm of Hurst exponent and Choquet integral with respect to extensional Lambda-measure was proposed. A real data set of the temperature of thermostable proteins with 5-fold cross-validation MSE was used for evaluation. The performances of the Choquet integral regression models based on extensional Lambdameasure, completed L-measure, Lambda-measure, and the P-measure, respectively, along with two traditional regression models, the multiple regression model and the ridge regression model were compared. The results show the integrated algorithm of Hurst exponent and Choquet integral regression model with respect to extensional Lambda-measure outperforms the others.

Original languageEnglish
Pages (from-to)1937-1942
Number of pages6
JournalICIC Express Letters
Volume7
Issue number6
Publication statusPublished - 2013 Jun 1

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science(all)

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