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

  • Pokkuluri Kiran Sree
  • Inampudi Ramesh Babu
  • S. S. S. N. Usha Devi Nedunuri
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 248)


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.


Promoter region Cellular Automata MACA 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Pokkuluri Kiran Sree
    • 1
  • Inampudi Ramesh Babu
    • 2
  • S. S. S. N. Usha Devi Nedunuri
    • 3
  1. 1.Department of Computer Science & EngineeringJawaharlal Nehru Technological Universtiy HyderabadKukatpallyIndia
  2. 2.Department of Computer Science & EngineeringAcharya Nagarjuna UniversityGunturIndia
  3. 3.Dept of CSEJawaharlal Nehru Technological UniverstiyKakinadaIndia

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