E.coli promoter recognition through wavelets

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Date
2008-12-01
Authors
Rani, T. Sobha
Bapi, Raju S.
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Abstract
RNA Polymerase binding to the promoter is the first step in gene transcription. A particular subunit of RNA polymerase is responsible for the recognition of TATA box in promoter. An attempt is made through signal analysis techniques to understand the behavior of the interaction between RNA polymerase sigma subunit and promoter. This information is used as a classification rule, in recognizing a promoter versus a non-promoter using a neural network classifier. Wavelet decomposition is used as the signal processing technique to analyze the E.coli promoter and the interaction between RNA polymerase sigma subunit and promoter. The interaction or cross-correlation between RNA polymerase sigma subunit and promoter is explored in the hope of finding the interaction useful. The classification results using this information are not so very good as compared to other techniques. Further, multi resolution analysis of promoter attempts to glean the specific information at a particular level of decomposition. Again the classification of non-promoters is very good, but the classification of promoters falls behind.
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Keywords
Machine learning, Neural networks, Promoter recognition, Promoter-RNA polymerase interaction, Wavelets
Citation
Proceedings of the 2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008