Title :
Protein Sequences Analysis Based on Smoothed PST
Author :
Liu, Yong ; Yan, Tuanjun ; Zhang, Rui
Author_Institution :
Inst. of Intell. Vision & Image, Inf. China Three Gorges Univ., Yichang, China
Abstract :
Sequence alignment algorithms, which are hardly to be efficient, are frequently used in protein sequences analysis. In order to improve the analyzing efficiency, an improved PST(Probabilistic Suffix Trees) model is proposed in this paper. Firstly, by analyzing the similarity between protein sequences analysis and sequences data mining, the idea of using PST model to analyze protein sequences is presented; And then the standard PST model is improved by smoothing operation according to the features of protein sequences analysis; Next, taking the smoothed PST as features of data set, the similarities degree between protein sequences are calculated by using the similarities of the normalized sequences; At last, the effectiveness and high efficiency of the algorithm are verified by some protein sequences analysis examples.
Keywords :
biology computing; data mining; molecular biophysics; probability; proteins; smoothing methods; trees (mathematics); data set feature; protein sequences analysis; sequence alignment algorithm; sequence data mining; smoothed probabilistic suffix tree model; Algorithm design and analysis; Data analysis; Data mining; Image analysis; Image sequence analysis; Information analysis; Predictive models; Protein sequence; Smoothing methods; Testing;
Conference_Titel :
Bioinformatics and Biomedical Engineering , 2009. ICBBE 2009. 3rd International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2901-1
Electronic_ISBN :
978-1-4244-2902-8
DOI :
10.1109/ICBBE.2009.5163257
