Title :
Clustering methods for accurate DNA base-calling
Author :
Manolakos, Elias S.
Author_Institution :
Dept. of Electr. & Comput. Eng., Northeastern Univ., Boston, MA, USA
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;
Conference_Titel :
Signals, Systems and Computers, 2002. Conference Record of the Thirty-Sixth Asilomar Conference on
Conference_Location :
Pacific Grove, CA, USA
Print_ISBN :
0-7803-7576-9
DOI :
10.1109/ACSSC.2002.1197197
