Genetic K-modes based DNA splice site adjacent sequences feature analysis

Author

Zhang, Quanwei ; Peng, Qinke ; Sun, Hequan ; Li, Kankan

Author_Institution

Sch. of Electron. & Inf. Eng., Xi´´an Jiaotong Univ., Xi´´an

fYear

2008

fDate

25-27 June 2008

Firstpage

2065

Lastpage

2070

Abstract

DNA splice site adjacent sequences have remarkable conservative feature, and mining their underlying biological knowledge has become a key issue in the field of DNA sequences analysis. In this paper, we analyze the feature of human beingpsilas DNA splice site adjacent sequences. Firstly, we propose a kind of DNA splice site sequences clustering method based on Genetic K-modes; secondly, we analyze the frequency of various bases, di-bases and tri-bases about the experimental data set and each cluster; lastly, we propose one kind of Markov model based frequent patterns discovery algorithm and use it to mine the frequent patterns of the experimental data set and each cluster.

Keywords

DNA; Markov processes; biology computing; data mining; feature extraction; genetic algorithms; pattern clustering; sequences; DNA splice site sequence clustering method; Markov model; biological knowledge mining; frequent pattern discovery algorithm; genetic K-mode algorithm; human being DNA splice site adjacent sequence feature analysis; Bioinformatics; Clustering algorithms; DNA; Frequency; Genetic engineering; Genomics; Humans; Information analysis; Knowledge engineering; Sequences; K-modes algorithm; Markov model; clustering; genetic algorithm; splice site;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on

Conference_Location

Chongqing

Print_ISBN

978-1-4244-2113-8

Electronic_ISBN

978-1-4244-2114-5

Type

conf

DOI

10.1109/WCICA.2008.4593242

Filename

4593242