Title :
A new protein structure classification model
Author :
Dong Wang ; Shiyuan Han ; Yuehui Chen ; Wenzheng Bao ; Kun Ma ; Abraham, Ajith
Author_Institution :
Sch. of Inf. Sci. & Eng., Univ. of Jinan, Jinan, China
fDate :
July 30 2014-Aug. 1 2014
Abstract :
Protein structure prediction is an important area of research in bioinformatics. In this paper, we select the features of correlation coefficient sequence and special amino acid composition. The support vector machine and a particular framework of ECOC are employed as classification model. To evaluate the efficiency of the proposed method we choose three benchmark protein sequence datasets (25PDB, 40PDB and ASTRAL) as the test dataset. The final results show that our method is efficient for protein structure prediction.
Keywords :
bioinformatics; feature selection; molecular configurations; pattern classification; proteins; support vector machines; ECOC; SVM; amino acid composition; bioinformatics; correlation coefficient sequence; feature selection; protein sequence datasets; protein structure classification model; protein structure prediction; support vector machine; Bayes methods; Classification algorithms; Proteins; ECOC; Prediction structure of protein; Support Vector machine;
Conference_Titel :
Computational Aspects of Social Networks (CASoN), 2014 6th International Conference on
Conference_Location :
Porto
Print_ISBN :
978-1-4799-5939-6
DOI :
10.1109/CASoN.2014.6920419
