Title :
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
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;
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
DOI :
10.1109/WCICA.2008.4593242
