IN-AIS-MACA: Integrated Artificial Immune System based Multiple Attractor Cellular Automata For Human Protein Coding and Promoter Prediction of 252bp Length DNA Sequence

Authors

  • Pokkuluri Kiran Sree

  • Pokkuluri Kiran Sree

  • Inampudi Ramesh Babu

Keywords:

IN-AIS-MACA, protein coding, promoter predictions, DNA sequences

Abstract

Gene prediction involves protein coding and promoter predictions. There is a need of integrated algorithms which can predict both these regions at a faster rate. Till date, we have individual algorithms for addressing these problems. We have developed a novel classifier IN-AIS-MACA, which can predict both these regions in genomic DNA sequences of length 252bp with 93.5% accuracy and total prediction time of 1031ms. This classifier will certainly create intuition to develop more classifiers like this.

How to Cite

Pokkuluri Kiran Sree, Pokkuluri Kiran Sree, & Inampudi Ramesh Babu. (2014). IN-AIS-MACA: Integrated Artificial Immune System based Multiple Attractor Cellular Automata For Human Protein Coding and Promoter Prediction of 252bp Length DNA Sequence. Global Journal of Computer Science and Technology, 14(G2), 1–9. Retrieved from https://computerresearch.org/index.php/computer/article/view/93

IN-AIS-MACA: Integrated Artificial Immune System based Multiple Attractor Cellular Automata For Human Protein Coding and Promoter Prediction of 252bp Length DNA Sequence

Published

2014-03-15