Cascaded multi-level Promoter recognition of E. coli using dinucleotide features
Cascaded multi-level Promoter recognition of E. coli using dinucleotide features
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Date
2008-12-01
Authors
Rani, T. Sobha
Bapi, Raju S.
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Abstract
Promoter recognition has been attempted using different paradigms such as motif/binding regions alone or whole promoter itself. In an earlier paper, a scheme is proposed to use 2-gramfeatures to represent a promoter. These 2-grams gave a comparable performance with the existing methods in the literature. An in-depth analysis of data sets using 2-grams is performed. The analysis presented a scenario where there is a confusion between a majority of promoters with a minor set of non-promoter and vice versa. In an effort to build a complete classification system, using the majority and minority sets in promoters as well as non-promoters, a multi-level cascading system and Ada-Boost classifier are applied. The results indicate that much further improvement is not possible with the modifications proposed. © 2008 IEEE.
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Keywords
Ada-Boost classifier,
Global feature extraction,
Machine learning techniques,
Neural networks
Citation
Proceedings - 11th International Conference on Information Technology, ICIT 2008