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

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

Contact

Inampudi Ramesh Babu

Contact

SSSN Usha Devi N

Contact

Jawaharlal Nehru Technological University, Kakinada

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

Article Fingerprint

ReserarchID

BAY32

AI TAKEAWAY

Connecting with the Eternal Ground

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

Reference Format

Teresa Attwood (2000). The Babel of bioinformatics.
James Fickett,Chang-Shung Tung (1992). Assessment of protein coding measures.
Riu Yamashita,Yutaka Suzuki,Hiroyuki Wakaguri,Katsuki Tsuritani,Kenta Nakai,Sumio Sugano (2006). DBTSS: database of human transcription start sites, progress report 2006.
Serge Saxonov,Iraj Daizadeh,Alexei Fedorov,Walter Gilbert (2000). EID: the Exon-Intron Database--an exhaustive database of protein-coding intron-containing genes.
Graziano Pesole,Sabino Liuni,Giorgio Grillo,Flavio Licciulli,Flavio Mignone,Carmela Gissi,Cecilia Saccone (2002). UTRdb and UTRsite: specialized databases of sequences and functional elements of 5' and 3' untranslated regions of eukaryotic mRNAs. Update 2002.
Pokkuluri Sree,Kiran,Ramesh Inampudi,Babu (2014). AIX-MACA-Y Multiple Attractor Cellular Automata Based Clonal Classifier for Promoter and Protein Coding Region Prediction.
Steven Salzberg (1995). Locating Protein Coding Regions in Human DNA Using a Decision Tree Algorithm.
Pradipta Maji,Sushmita Paul (2014). Neural Network Tree for Identification of Splice Junction and Protein Coding Region in DNA.
Ying Xu,R Mural,M Shah,E Uberbacher (1993). Recognizing exons in genomic sequence using GRAIL II.
Eric Snyder,Gary Stormo (1995). Identification of protein coding regions in genomic DNA.
Edward Uberbacher,Richard Mural (1991). Locating protein-coding regions in human DNA sequences by a multiple sensor-neural network approach..
Armando Pinho,A Neves,V Afreixo,C Bastos,P Ferreira (2006). A Three-State Model for DNA Protein-Coding Regions.
M Zhang (1997). Identification of protein coding regions in the human genome by quadratic discriminant analysis.
Sridhar Hannenhalli,Samuel Levy (2001). Promoter prediction in the human genome.
Shuanhu Wu,Xudong Xie,Alan Wee-Chung Liew,Hong Yan (2007). Eukaryotic promoter prediction based on relative entropy and positional information.
Uwe Ohler,Heinrich Niemann,Guo-Chun Liao,Gerald Rubin (2001). Joint modeling of DNA sequence and physical properties to improve eukaryotic promoter recognition.
J Goñi,Alberto Pérez,David Torrents,Modesto Orozco (2007). Determining promoter location based on DNA structure first-principles calculations.
Vladimir Bajic,Hong Seng,Allen Seah,Guanglan Chong,Judice Zhang,Vladimir Ly Koh,Brusic (2002). Dragon Promoter Finder: recognition of vertebrate RNA polymerase II promoters.
Michael Zhang (1998). Identification of Human Gene Core Promoters in Silico.
Jia Zeng,Xiao-Yu Zhao,Xiao-Qin Cao,Hong Yan (2010). SCS: Signal, context, and structure features for genome-wide human promoter recognition.
Xiaomeng Li,Jia Zeng,Hong Yan ; Gish,Warren,David States (1993). Identification of protein coding regions by database similarity search.

Download References

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. 2014. \u201cIN-AIS-MACA: Integrated Artificial Immune System based Multiple Attractor Cellular Automata For Human Protein Coding and Promoter Prediction of 252bp Length DNA Sequence\u201d. Global Journal of Computer Science and Technology - G: Interdisciplinary GJCST-G Volume 14 (GJCST Volume 14 Issue G2): .

More Citation Formats

Select Citation Style:

Download Citation

Download Article

GJCST Volume 14 Issue G2
Pg. 1- 9

Explore Journals Explore Volume Read This Issue

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

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

Experiance in AR

Explore published articles in an immersive Augmented Reality environment. Our platform converts research papers into interactive 3D books, allowing readers to view and interact with content using AR and VR compatible devices.

View in VR

Read in 3D

Your published article is automatically converted into a realistic 3D book. Flip through pages and read research papers in a more engaging and interactive format.

View in 3D

Article Matrices

Total Score: 103

Country: India

Subject: Global Journal of Computer Science and Technology - G: Interdisciplinary

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

View Count (all-time): 273

Total Views (Real + Logic): 8865

Total Downloads (simulated): 2211

Publish Date: 2014 09, Thu

Monthly Totals (Real + Logic):

Month 1: 28 views
Month 2: 48 views
Month 3: 46 views
Month 4: 31 views
Month 5: 21 views
Month 6: 46 views
Month 7: 49 views
Month 8: 17 views
Month 9: 33 views
Month 10: 30 views
Month 11: 39 views
Month 12: 41 views
Month 13: 28 views
Month 14: 26 views
Month 15: 31 views
Month 16: 27 views
Month 17: 24 views
Month 18: 30 views
Month 19: 37 views
Month 20: 33 views
Month 21: 28 views
Month 22: 42 views
Month 23: 39 views
Month 24: 36 views
Month 25: 27 views
Month 26: 40 views
Month 27: 42 views
Month 28: 33 views
Month 29: 36 views
Month 30: 47 views
Month 31: 14 views
Month 32: 41 views
Month 33: 18 views
Month 34: 18 views
Month 35: 16 views
Month 36: 35 views
Month 37: 17 views
Month 38: 33 views
Month 39: 40 views
Month 40: 27 views
Month 41: 22 views
Month 42: 43 views
Month 43: 21 views
Month 44: 34 views
Month 45: 25 views
Month 46: 41 views
Month 47: 28 views
Month 48: 16 views
Month 49: 16 views
Month 50: 36 views
Month 51: 38 views
Month 52: 30 views
Month 53: 14 views
Month 54: 26 views
Month 55: 29 views
Month 56: 26 views
Month 57: 28 views
Month 58: 34 views
Month 59: 45 views
Month 60: 21 views
Month 61: 15 views
Month 62: 49 views
Month 63: 45 views
Month 64: 31 views
Month 65: 25 views
Month 66: 36 views
Month 67: 34 views
Month 68: 41 views
Month 69: 35 views
Month 70: 36 views
Month 71: 22 views
Month 72: 26 views
Month 73: 23 views
Month 74: 41 views
Month 75: 34 views
Month 76: 24 views
Month 77: 36 views
Month 78: 27 views
Month 79: 34 views
Month 80: 24 views
Month 81: 35 views
Month 82: 40 views
Month 83: 37 views
Month 84: 26 views
Month 85: 21 views
Month 86: 30 views
Month 87: 33 views
Month 88: 27 views
Month 89: 33 views
Month 90: 21 views
Month 91: 11 views
Month 92: 39 views
Month 93: 41 views
Month 94: 30 views
Month 95: 20 views
Month 96: 26 views
Month 97: 42 views
Month 98: 34 views
Month 99: 26 views
Month 100: 32 views
Month 101: 28 views
Month 102: 17 views
Month 103: 24 views
Month 104: 21 views
Month 105: 35 views
Month 106: 32 views
Month 107: 43 views
Month 108: 35 views
Month 109: 41 views
Month 110: 21 views
Month 111: 40 views
Month 112: 33 views
Month 113: 21 views
Month 114: 26 views
Month 115: 19 views
Month 116: 35 views
Month 117: 18 views
Month 118: 22 views
Month 119: 19 views
Month 120: 37 views
Month 121: 29 views
Month 122: 38 views
Month 123: 40 views
Month 124: 25 views
Month 125: 29 views
Month 126: 35 views
Month 127: 23 views
Month 128: 20 views
Month 129: 48 views
Month 130: 38 views
Month 131: 39 views
Month 132: 29 views
Month 133: 35 views
Month 134: 23 views
Month 135: 31 views
Month 136: 43 views
Month 137: 33 views
Month 138: 29 views
Month 139: 48 views
Month 140: 39 views

Total Views: 8865

Total Downloads: 2211

2026 Trends

Published Article

Our website is actively being updated, and changes may occur frequently. Please clear your browser cache if needed. For feedback or error reporting, please email [email protected]