DocumentCode :
2088892
Title :
Cascaded Multi-level Promoter Recognition of  E. coli Using Dinucleotide Features
Author :
Rani, T. Sobha ; Bapi, Raju S.
Author_Institution :
Dept. of Comput. & Inf. Sci., Univ. of Hyderabad, Hyderabad, India
fYear :
2008
fDate :
17-20 Dec. 2008
Firstpage :
83
Lastpage :
88
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-gram features 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.
Keywords :
biology computing; data analysis; microorganisms; pattern classification; 2-gram features; Ada-Boost classifier; E. coli; cascaded multilevel promoter recognition; complete classification system; data analysis; data sets; dinucleotide features; in-depth analysis; majority sets; minority sets; motif/binding regions; multilevel cascading system; Computational intelligence; Data analysis; Feature extraction; Frequency; Gene expression; Information technology; Machine learning; Neural networks; Performance analysis; Switches; Ada-boost classifier; global feature extraction; machine learning techniques; neural networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Technology, 2008. ICIT '08. International Conference on
Conference_Location :
Bhubaneswar
Print_ISBN :
978-1-4244-3745-0
Type :
conf
DOI :
10.1109/ICIT.2008.56
Filename :
4731304
Link To Document :
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