Title :
An improved CBA prediction algorithm in compound pyramid model
Author :
Zhun, Zhou ; Bingru, Yang ; Wei, Hou
Author_Institution :
Inf. Eng. Sch., Univ. of Sci. & Technol. Beijing, Beijing, China
Abstract :
As one of KDTICM theory researches, this paper propose an improved algorithm - CBA, which is based on KDD* model and combined with KAAPRO method, for protein secondary structure prediction problem. Further, multilayer systematic prediction model--compound pyramid model, is proposed. The kernel of this model is CBA which is a classic association rules analysis algorithm. Domain knowledge is used through the model, and the phy-chemical attributes is chosen by causal cellular automation. In experiment, the proteins bias alpha/beta structure are precisely predicted. The structures of amino acids, whose structure are obscure, are predicted well by the improved CBA. Finally, the result of this model is satisfied.
Keywords :
biology computing; cellular automata; physiological models; prediction theory; proteins; proteomics; CBA prediction algorithm; KAAPRO method; KDD* model; KDTICM theory; alpha/beta structure; amino acids; causal cellular automation; compound pyramid model; protein secondary structure; Accuracy; Algorithm design and analysis; Amino acids; Association rules; Bioinformatics; Data mining; Databases; Prediction algorithms; Predictive models; Protein engineering; Association Rule; CBA algorithm; Compound Pyramid Model; Protein secondary structure Prediction;
Conference_Titel :
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-2722-2
Electronic_ISBN :
978-1-4244-2723-9
DOI :
10.1109/CCDC.2009.5194999
