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

Authors:
Yasuo Matsuyama;Ryo Kawamura
Affiliations:
Waseda University;Sony-Kihara Research Center Inc.
Venue:
CSB '04 Proceedings of the 2004 IEEE Computational Systems Bioinformatics Conference
Year:
2004

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Abstract

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.