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.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004 |
| Pages | 686-691 |
| Number of pages | 6 |
| Publication status | Published - 2004 |
| Event | Proceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004 - Stanford, CA Duration: 2004 Aug 16 → 2004 Aug 19 |
Other
| Other | Proceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004 |
|---|---|
| City | Stanford, CA |
| Period | 04/8/16 → 04/8/19 |
ASJC Scopus subject areas
- Engineering(all)
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Cite this
Matsuyama, Y., & Kawamura, R. (2004). Promoter recognition for E. coli DNA segments by independent component analysis. In Proceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004 (pp. 686-691)