Cascaded multi-level Promoter recognition of E. coli using dinucleotide features

dc.contributor.author Rani, T. Sobha
dc.contributor.author Bapi, Raju S.
dc.date.accessioned 2022-03-27T05:50:52Z
dc.date.available 2022-03-27T05:50:52Z
dc.date.issued 2008-12-01
dc.description.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.
dc.identifier.citation Proceedings - 11th International Conference on Information Technology, ICIT 2008
dc.identifier.uri 10.1109/ICIT.2008.56
dc.identifier.uri http://ieeexplore.ieee.org/document/4731304/
dc.identifier.uri https://dspace.uohyd.ac.in/handle/1/8268
dc.subject Ada-Boost classifier
dc.subject Global feature extraction
dc.subject Machine learning techniques
dc.subject Neural networks
dc.title Cascaded multi-level Promoter recognition of E. coli using dinucleotide features
dc.type Conference Proceeding. Conference Paper
dspace.entity.type
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