Promoter Recognition for E. coli DNA Segments by Independent Component Analysis

CC
CSB
2004
2004 IEEE Computational Systems Bioinformatics Conference (CSB'04)
Abstract - Promoter Recognition for E. coli DNA Segments by Independent Component Analysis

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	Similar Articles Articles by Yasuo Matsuyama Articles by Ryo Kawamura

2004 IEEE Computational Systems Bioinformatics Conference (CSB'04)

Stanford, California

August 16-August 19

ISBN: 0-7695-2194-0

	ASCII Text	x
	Yasuo Matsuyama, Ryo Kawamura, "Promoter Recognition for E. coli DNA Segments by Independent Component Analysis," Computational Systems Bioinformatics Conference, International IEEE Computer Society, pp. 686-691, 2004 IEEE Computational Systems Bioinformatics Conference (CSB'04), 2004.

	BibTex	x
	@article{ 10.1109/CSB.2004.1332546, author = {Yasuo Matsuyama and Ryo Kawamura}, title = {Promoter Recognition for E. coli DNA Segments by Independent Component Analysis}, journal ={Computational Systems Bioinformatics Conference, International IEEE Computer Society}, volume = {0}, year = {2004}, isbn = {0-7695-2194-0}, pages = {686-691}, doi = {http://doi.ieeecomputersociety.org/10.1109/CSB.2004.1332546}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Computational Systems Bioinformatics Conference, International IEEE Computer Society TI - Promoter Recognition for E. coli DNA Segments by Independent Component Analysis SN - 0-7695-2194-0 SP686 EP691 A1 - Yasuo Matsuyama, A1 - Ryo Kawamura, PY - 2004 KW - null VL - 0 JA - Computational Systems Bioinformatics Conference, International IEEE Computer Society ER -

Yasuo Matsuyama, Waseda University

Ryo Kawamura, Sony-Kihara Research Center Inc.

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSB.2004.1332546

A new method for E. coli DNA segment classification on promoters and non-promoters is presented. The algorithm is based on the Independent Component Analysis (ICA). Since the DNA segments are composed of discrete symbols, this paper contains two major steps: (1) Position-dependent transformation of DNA segments to real number sequences, and (2) Applications of the ICA to the E. coli promoter recognition. These steps are related to each other. Therefore, algorithmic explanations are given in detail while referring mutually. The automatic precision of 93.7% is obtained. Since the presented method allows threshold adjustments, twilight-zone data can be further cross-checked individually so that false negatives are reduced.

Citation:

Yasuo Matsuyama, Ryo Kawamura, "Promoter Recognition for E. coli DNA Segments by Independent Component Analysis," csb, pp.686-691, 2004 IEEE Computational Systems Bioinformatics Conference (CSB'04), 2004

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