DNA is a very important component in a cell, which is located in the nucleus. DNA contains lot of information. For DNA sequence to transcript and form RNA which copies the required information, we need a promoter. So 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 the 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 in eukaryotes. We have used three important features like TATA box, GC box and CAAT box for developing this classifier. We have also used context future 6-mer for predicting the same. The proposed classifier is trained and tested with datasets from DBTSS, EID, UTRdb datasets . In training phase of the classifier 100% specificity was obtained. In testing phase 84.5% sensitivity and 92.7% specificity was achieved in an average. The time taken to predict the promoter region of length 252 in an average is 4 micro seconds.
Author(s): Pokkuluri Kiran Sree and Inampudi Ramesh Babu