Clustering methods for accurate DNA base-calling

Author

Manolakos, Elias S.

Author_Institution

Dept. of Electr. & Comput. Eng., Northeastern Univ., Boston, MA, USA

Volume

1

fYear

2002

fDate

3-6 Nov. 2002

Firstpage

311

Abstract

Routinely extending the useful read-lengths of DNA chromatograms beyond 1 kps by employing intelligent base-calling algorithms will be extremely useful to genomics research because in many cases the entire coding region of a gene could fit into a single long read. By segmenting the chromatograms into base-call "events" to be labeled in terms of the number of bases they represent, base-calling as a pattern classification problem is formulated. An overview of two unsupervised clustering methods that could be used for its solution is presented.

Keywords

DNA; biological techniques; chromatography; feature extraction; genetics; pattern clustering; BEM base-caller; DNA chromatograms; TBC base-caller; automated DNA sequencing; clustering methods; gene coding; genomics; intelligent base-calling algorithms; pattern classification; read-lengths; unsupervised clustering; Clustering algorithms; Clustering methods; DNA; Data mining; Detectors; Digital signal processing; Electrokinetics; Sequences; Signal processing; Signal processing algorithms;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems and Computers, 2002. Conference Record of the Thirty-Sixth Asilomar Conference on

Conference_Location

Pacific Grove, CA, USA

ISSN

1058-6393

Print_ISBN

0-7803-7576-9

Type

conf

DOI

10.1109/ACSSC.2002.1197197

Filename

1197197