MACA-MCC-DA: A Fast MACA with Modified Clonal Classifier Promoter Region Prediction in Drosophila and Arabidopsis
Pokkuluri Kiran Sree, Inampudi Ramesh Babu
DNA is a very important component in a cell, which is located in the nucleus. DNA contains lots of information. For DNA sequence to transcript and form RNA, which copies the required information, we need a promoter. So a promoter plays a vital role in DNA transcription. It is defined as “the sequence in the region of the upstream of the transcriptional start site (TSS)”. If we identify a promoter region, we can extract information regarding gene expression patterns, cell specificity and development. So we propose a novel fast multiple attractor cellular automata (MACA) with modified Clonal classifier for promoter prediction for Drosophila and Arabidopsis. We have used three important features like TATA box, GC box and CAAT box for developing this classifier. We have also used 3-mers and 6-mers for predicting the promoters. The proposed classifier is tested with datasets from Berkeley Drosophila database for drosophila and TAIR Arabidopsis thaliana database. We have achieved an average classifier accuracy more than 89.6% for Drosophila and 92.6 for Arabidopsis.
Pokkuluri Kiran Sree, Inampudi Ramesh Babu . MACA-MCC-DA: A Fast MACA with Modified Clonal Classifier Promoter Region Prediction in Drosophila and Arabidopsis. European Journal of Biotechnology and Bioscience, Volume 1, Issue 6, 2014, Pages 22-26