Transmembrane helix prediction using feed-forward neural network

Author

Mottalib, M.A. ; Mahdi, M.S.R. ; Haque, A.B.M.Z. ; Al Mamun, S.M. ; Al Mamun, H.A.

Author_Institution

Dept. of Comput. Sci. & Inf. Technol. (CIT), Islamic Univ. of Technol. (IUT), Gazipur, Bangladesh

fYear

2009

fDate

21-23 Dec. 2009

Firstpage

598

Lastpage

602

Abstract

Neural network is one of the successful methods for protein secondary structure prediction. Day to day this technology is modified, improved, even other methods also combined with it to get better result. In this paper we trained feed-forward neural network with trans-membrane protein for helix prediction. Using Java object oriented neural engine (JOONE) our achieved accuracy is 71%. This paper is expected to benefit researchers in proteomics by presenting a summary of developments of neural network in this area.

Keywords

Java; biology computing; feedforward neural nets; search engines; Java object oriented neural engine; feedforward neural network; protein secondary structure prediction; proteomics; transmembrane helix prediction; Amino acids; Bioinformatics; Biological neural networks; Biology computing; Biomembranes; Feedforward neural networks; Feedforward systems; Information technology; Neural networks; Proteins; a-helix; bioinformatics; feed-forward neural network; transmembrane protein;

fLanguage

English

Publisher

ieee

Conference_Titel

Computers and Information Technology, 2009. ICCIT '09. 12th International Conference on

Conference_Location

Dhaka

Print_ISBN

978-1-4244-6281-0

Type

conf

DOI

10.1109/ICCIT.2009.5407307

Filename

5407307