Discriminating DNA Sequences from Terahertz Spectroscopy - A Wavelet Domain Analysis

Author

Weng, Binwei ; Xuan, Guangchi ; Kolodzey, J. ; Barner, K.E.

Author_Institution

Department of Electrical and Computer Engineering, University of Delaware, Newark, DE 19716, USA

fYear

2006

fDate

2006

Firstpage

211

Lastpage

212

Abstract

DNA sequence analysis has been widely studied by geneexpression microarray techniques. Few results, however, have been provided by Terahertz spectroscopy which reveals the absorbtion or reflectance percentage from different DNA sequences. Previous Terahertz methods have lacked a quantitative analysis of the spectroscopy features, and no definitive conclusion regarding the data can be easily drawn. In this paper, we use a data clustering approach which gives a quantitative interpretation of the DNA spectroscopy. The wavelet transform is applied to extract features from the original measurements. The data is subsequently partitioned by a hierarchical clustering method. Experimental results of Terahertz spectroscopy of several different DNA samples show that the wavelet domain analysis aids the clustering process and yields clustering of higher validity than that obtained from the raw data.

Keywords

Clustering methods; DNA; Data mining; Feature extraction; Reflectivity; Sequences; Spectroscopy; Wavelet analysis; Wavelet domain; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioengineering Conference, 2006. Proceedings of the IEEE 32nd Annual Northeast

Conference_Location

Easton, PA, USA

Print_ISBN

0-7803-9563-8

Type

conf

DOI

10.1109/NEBC.2006.1629827

Filename

1629827