Application of Takagi-Sugeno model in the recognition of splice sites

被引：0

作者：

Guo, Shuo ^{[1
,2
]}

Zhu, Yi-Sheng ^{[1
]}

机构：

[1] College of Information Engineering, Dalian Maritime University, Dalian 116026, China

[2] College of Information Engineering, Shenyang Institute of Chemical Technology, Shenyang 110142, China

来源：

Dalian Haishi Daxue Xuebao/Journal of Dalian Maritime University | 2007年 / 33卷 / 04期

关键词：

Clustering algorithms - Computational complexity - Fuzzy sets - Least squares approximations - Mathematical models;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

To reduce the computational complexity of the recognition of splice site, a Takagi-Sugeno fuzzy model was constructed based on the feature of the conservative signal sequences and the statistical characteristics of base composition varying with GC content in up-and-down stream sequences around splice sites. A true split site was determined by comparing output and threshold value of the model. Clustering algorithm based on the fuzzy likelihood function was used to determine the structure and the premise parameters of the Takagi-Sugeno fuzzy model, which the conclusion parameters of the model was identified by least squares method. The proposed method can identify the structure and the parameters of the fuzzy model at the same time. Simulation results show the method is effective at retrieving the statistical characteristics of the conserved sequences around splicing sites. The algorithm provides a new clue for the recognition of splice site.

引用

页码：60 / 64