Accession number:20094612446812
Title: A novel predicting algorithm of thermostable proteins based on choquet integral with respect to L-measure and hurst exponent
Authors: Shieh, Jiunn-I (1); Liu, Yu-Lung (2); Lee, Kuei-Jen (3); Chang, Pei-Chun (3); Liu, Yi-Cheng (3)
Author affiliation:(1) Department of Information Science and
Applications, Asia University, Taiwan; (2) Department of Computer Science and Information Engineering, Asia University, Taiwan; (3) Department of Bioinformatics, Asia University, Taiwan
Corresponding author:Shieh, J.-I.
Source title: Proceedings of the 2009 International Conference on Machine Learning and Cybernetics
Abbreviated source title:Proc. Int. Conf. Mach. Learn. Cybern.
Volume:6
Monograph title:Proceedings of the 2009 International Conference on Machine Learning and Cybernetics
Issue date:2009
Publication year:2009 Pages:3167-3171
Article number:5212804 Language:English
ISBN-13:9781424437030
Document type:Conference article (CA)
Conference name:2009 International Conference on Machine Learning and Cybernetics
Conference date:July 12, 2009 - July 15, 2009 Conference location:Baoding, China
Conference code:78063
Publisher:IEEE Computer Society, 445 Hoes Lane - P.O.Box 1331, Piscataway, NJ 08855-1331, United States
Abstract:Establishing a good algorithm for predicting temperature of thermostable proteins is an important issue. In this study, a novel thermostable proteins prediction method using Hurst exponent and Choquet integral regression model based on L-measure and
γ-support is proposed. The main idea of this method is to integrate the physicochemical properties, fractal property and
Choquet integral regression model for amino symbolic sequences with different lengths. For evaluating the performance of this new algorithm, a 5-fold Cross-Validation MSE is performed. Experimental result shows that this new prediction scheme is better than the Choquet integral regression model based on λ-measure and P-measure, respectively and two methods based on Hurst exponent and the traditional prediction models, ridge regression and multiple regression model, respectively. © 2009 IEEE.
Number of references:12
Main heading:Regression analysis
Controlled terms: Amines - Control theory - Cybernetics - Integral equations - Mathematical models - Proteins - Robot learning
Uncontrolled terms: Choquet integral - Cross validation - Fractal properties - Hurst exponent - Hurst exponents - L-measure - Multiple regression model - P-measure - Physicochemical property -
Prediction methods - Prediction model - Prediction schemes - Regression model - Ridge regression - Singleton measures - Symbolic sequence
Classification code:921.2 Calculus - 921 Mathematics - 804.1
Organic Compounds - 922.2 Mathematical Statistics - 731.5 Robotics - 723.4 Artificial Intelligence - 461.9 Biology - 731.1 Control Systems DOI:10.1109/ICMLC.2009.5212804
Database:Compendex
Compilation and indexing terms, Copyright 2009 Elsevier Inc.
