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

Pokkuluri Kiran Sree; Inampudi Ramesh Babu

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

Pokkuluri Kiran Sree * §

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Inampudi Ramesh Babu

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§ University College of Engineering

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

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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.

References

21 Cites in Article

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

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 - G: Interdisciplinary GJCST-G Volume 14 (GJCST Volume 14 Issue G2).

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GJCST Volume 14 Issue G2

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

DNA sequences IN-AIS-MACA promoter predictions protein coding

Classification

B.6.1

B.7

Submission ReceivedDecember 12, 2013
Peer Review Double Blind
Handling Editor
Accepted January 4, 2014
Published January 15, 2014

Version of record

v1.2

Issue date

September 18, 2014

Language

English

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Article Matrices

Total Score: 143

Country: India

Subject: Global Journal of Computer Science and Technology

Authors: Pokkuluri Kiran Sree, Inampudi Ramesh Babu, SSSN Usha Devi N (PhD/Dr. count: 0)

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