AIS-PRMACA: Artificial Immune System based Multiple Attractor Cellular Automata for Strengthening PRMACA, Promoter Region Identification

Abstract

Identifying promoter region is an important problem in bioinformatics. Transcription of particular gene of DNA is initiated by a promoter. So many techniques are employed in identifying these promoter regions but all of them will attract an average accuracy of 84%. A new algorithm based on artificial immune system AIS-PRMACA was proposed to strengthen and improve the accuracy of promoter prediction system PRMACA. The proposed classifier is tested with BDGP and ENCODE data sets has produced an accuracy of 90.5% which is a considerable improvement when compared with the accuracy of conventional methods available.