Classification of DNA Sequences Basing on the Dinucleotide Compositions

Author

You, Wei ; Wang, Kun ; Li, Huixiao ; Jia, Yang ; Wu, Xiaoqin ; Du, Yaning

Author_Institution

Dept. of Mech. & Electr. Eng., North China Inst. of Sci. & Technol., Beijing, China

Volume

2

fYear

2009

fDate

12-14 Dec. 2009

Firstpage

390

Lastpage

394

Abstract

DNA sequences of several bacteria were classified using artificial neural network model. The Â¿dinucleotides compositionsÂ¿ method was used to characterize the DNA sequences which transform every DNA sequence to a 16-dimension vector. Back-propagation artificial neural network was developed and trained using Â¿leave-one-outÂ¿ method. Results showed that the accuracy of classification was 84.3%, which proved that the model was satisfactory in summary. However, the author stated that the applicability of the characterization strategy needs to be improved.

Keywords

DNA; backpropagation; biology computing; biotechnology; data analysis; microorganisms; neural nets; pattern classification; DNA sequence classification; backpropagation artificial neural network; bacteria; dinucleotide composition; leave-one-out method; Artificial neural networks; Bioinformatics; Computational intelligence; Computer errors; DNA; Genomics; Microorganisms; Predictive models; Sequences; Statistical analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Design, 2009. ISCID '09. Second International Symposium on

Conference_Location

Changsha

Print_ISBN

978-0-7695-3865-5

Type

conf

DOI

10.1109/ISCID.2009.244

Filename

5371066