PRMACA: A Promoter Region Identification Using Multiple Attractor Cellular Automata (MACA)

Abstract

Promoter region identification from sequences of DNA has gained a remarkable attention in recent years. Even though there are some identification techniques addressing this problem, the approximate accuracy in identifying the promoter region is closely 70% to 72%. An automated procedure was evolved with MACA (Multiple Attractor Cellular Automata) for identifying promoter regions. We have tested the proposed classifier ENCODE benchmark datasets with over three dozens of modern competing predictors shows that proposed algorithm (PRMACA) provides the best overall accuracy that ranges between 77% and 88.7%. PRMACA can identify promoter region with DNA or Amino acid sequences as inputs.