DocumentCode :
3305127
Title :
Protein Structure Classification Based on Chaos Game Representation and Multifractal Analysis
Author :
Yang, Jian-Yi ; Yu, Zu-Guo ; Anh, Vo
Author_Institution :
Sch. of Math. & Comput. Sci., Xiangtan Univ., Xiangtan
Volume :
4
fYear :
2008
fDate :
18-20 Oct. 2008
Firstpage :
665
Lastpage :
669
Abstract :
Classification of protein structures is important in the prediction of the tertiary structures of proteins. In this paper, we propose to decompose the chaos game representation of proteins in to two time series, from which the protein sequences can be uniquely reconstructed. Multifractal analysis is applied to measures constructed from these two time series. A total of 26 characteristic parameters are calculated for each protein, which are used to construct a 26-dimensional space. Each protein is represented by one point in this space. A procedure is proposed to classify the structures of 100 large proteins consisting of four structural classes. Fisher´s linear discriminant algorithmdemonstrates that the average accuracy for our classification can reach 84.67%. Compared with the results for the 46 large proteins reported before, the method proposed here has much better performance.
Keywords :
graph theory; image classification; image reconstruction; image representation; macromolecules; medical image processing; proteins; Fisher´s linear discriminant algorithm; chaos game representation; multifractal analysis; protein structure classification; Amino acids; Australia; Chaos; Fractals; Linear discriminant analysis; Mathematics; Proteins; Time measurement; Time series analysis; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-0-7695-3304-9
Type :
conf
DOI :
10.1109/ICNC.2008.295
Filename :
4667367
Link To Document :
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