Mining Protein Primary Structure Data Using Committee Machines Approach to Predict Protein Contact Map

Author

Habibi, N.K. ; Mahdaviani, Kaveh ; Saraee, M.H.

Author_Institution

Dept. of Electr. & Comput. Eng., Isfahan Univ. of Technol., Isfahan

fYear

2008

fDate

18-19 Oct. 2008

Firstpage

280

Lastpage

285

Abstract

Committee machines approach has shown to be useful in different applications. Protein primary structure data contain valuable information to extract. In this paper we mine these data and predict protein contact map based on committee machines. Contact map is the simplified, two dimensional representation of protein spatial structure. Contact map prediction is of great interest due to its application in fold recognition and predicting protein tertiary structure. The results show that the performance of the committee is considerably better than a single model.

Keywords

biology computing; data mining; prediction theory; proteins; committee machines; contact map prediction; data mining; protein contact map; protein primary structure data; protein spatial structure; Bioinformatics; Contacts; Data mining; Database systems; Genetic mutations; IEEE members; Laboratories; Machine learning; Protein engineering; Protein sequence; artificial intelligence; bioinformatics; committee machine; contact map prediction; ensemble learning; machine learning; neural network; protein contact map;

fLanguage

English

Publisher

ieee

Conference_Titel

Emerging Technologies, 2008. ICET 2008. 4th International Conference on

Conference_Location

Rawalpindi

Print_ISBN

978-1-4244-2210-4

Electronic_ISBN

978-1-4244-2211-1

Type

conf

DOI

10.1109/ICET.2008.4777515

Filename

4777515