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