We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 November 2024
Reseach Article

Automating Identification of Unique Patterns, Mutation in Human DNA using Artificial Intelligence Technique

by B.Mukunthan, Dr. N.Nagaveni
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 25 - Number 2
Year of Publication: 2011
Authors: B.Mukunthan, Dr. N.Nagaveni
10.5120/3003-4038

B.Mukunthan, Dr. N.Nagaveni . Automating Identification of Unique Patterns, Mutation in Human DNA using Artificial Intelligence Technique. International Journal of Computer Applications. 25, 2 ( July 2011), 26-34. DOI=10.5120/3003-4038

@article{ 10.5120/3003-4038,
author = { B.Mukunthan, Dr. N.Nagaveni },
title = { Automating Identification of Unique Patterns, Mutation in Human DNA using Artificial Intelligence Technique },
journal = { International Journal of Computer Applications },
issue_date = { July 2011 },
volume = { 25 },
number = { 2 },
month = { July },
year = { 2011 },
issn = { 0975-8887 },
pages = { 26-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume25/number2/3003-4038/ },
doi = { 10.5120/3003-4038 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:10:44.260098+05:30
%A B.Mukunthan
%A Dr. N.Nagaveni
%T Automating Identification of Unique Patterns, Mutation in Human DNA using Artificial Intelligence Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 25
%N 2
%P 26-34
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In molecular biology and genetic engineering, DNA sample identification is not considered as a biometric recognition technology mainly because it’s not an automated process i.e. it takes more time to analyze the DNA samples. Mutation identification is still an exigent task as it’s a manual process; mutations are changes in a genomic sequence caused by factors such as radiation, mutagenic chemicals, viruses, transposons. The automation of DNA feature extraction process achieved by applying neural network technique which has the advantage over conventional programming, in their ability to solve problem that do not have an algorithmic solution or the available solutions is too complex to be found is discussed in this paper, the proposed technique reduces the complication in precisely analyzing, interpreting the unique repeated patterns of human DNA. In this novel approach the perfect blend made of bioinformatics and neural networks technique results in efficient DNA pattern analysis algorithm with utmost prediction accuracy of unique repeated patterns and mutation, computed by number of correct identification of the target for a set of given inputs.

References
  1. Richard O. Duda, Peter E.Hart, David G. Stork, “Pattern classification”-Second Edition”, John Wiley and sons, 2006.
  2. Robert Schalkoff, “Pattern Recognition: Statistical, Structural and Neural Approaches, 2007, John Wiley and sons.
  3. Donald R. Tveter. “The Pattern Recognition Basis of Artificial Intelligence”, IEEE Press, New York, page 117.
  4. John Hertz, Anders Krogh, and Richard G. Palmer. “Introduction to the Theory of Neural Computation”, Addison Wesley, Redwood City, A, 2008.
  5. Stephen J. Hanson, Jack D. Cowan, and C. Lee Giles, “Advances in Neural Information Processing Systems”, volume 5, Morgan Kaufmann San Mateo CA, 2009.
  6. “Advances in Neural Networks issn-2006”, Third international symposium on neural networks, Springer Berlin Heidelberg, New York publications.
  7. Carpenter, G.A. and S. Grossberg, “A Massively Parallel Architecture for a self-organizing Neural Pattern Recognition Machine”, Computer Vision, Graphics and Image Processing, 37, PP. 54-115.
  8. Carpenter, G.A. and S. Grossberg, and J.H. Reynolds (2010), “ARTMAP: Supervised Real Time Learning and Classification of Non-stationary Data by a Self- organizing Neural Network”. Vol. 4, pp. 565-588.
  9. Stephen Krawetz, David D.Womble , “Introduction to Bioinformatics A Theoretical and Practical Approach”, Human Press Inc.,
  10. David W.Mount, David W. Mount, “Bio informatics Sequence and Genome analysis”- Second Edition, Cold Spring Harbor Laboratory Press, New York.
  11. Des Higgins, willie Taylor, “Bioinformatics Sequence, Structure and data banks”, Oxford University Press, 2000.
  12. “Bioinformatics for geneticists”, Michael R.Barnes , Second Edition, John Wiley & Sons Ltd.
  13. Andreas D. Buxevanis, “Bioinformatics-A practical Guide to the Analysis of genes and proteins”, second edition, A John wiley & sons, Inc., Publication.
  14. Norah Rudin, Keith Inman, “An Introduction forensic DNA Analysis”, 2002-CRC Press.
  15. .Computational Intelligence and Bio inspired Systems, 8th international work conference on artificial neural networks, iwann-2005proceedings.
  16. Julie A. Ayala-Gross, “DNA Analysis: The best method for Human Identifications”, National University, San Diego – 2001.
  17. Joe Nickell and John F.Fischar, “Crime Science Methods of Forensic Detection”, 1999. University Press of Kentucky.
  18. John O. Savino, Brent E Turvey , “Rape Investigation Hand book”, 2005, Elsevier Inc.,
  19. David E. Newton, “DNA Evidence and Forensic science”- 2008 facts on file, Inc. http://www.factsonfile.com.
  20. Jorg T. Epplen Thomas Lubjuhn, Birkhauser, “DNA Profiling and DNA Finger Printing”, Verlag Publication.
  21. Charles L.Valon, “New developments in Mutation Research”, Nova science publishers Inc New York, 2007.
  22. “Oxidative Damage to Nucleic Acids”, Springer science press, New York.
  23. Richard G. H. Cotton, Edward Edkins, Sue Forrest “Mutation detection”, IRL Press at Oxford University Press.
  24. Graham R. Taylor “Laboratory methods for the detection of mutations and polymorphisms in DNA”, CRC Press, 2007 - Science.
  25. Phipps Arabie, Lawrence J. Hubert, and Geert De Soete, editors, “Clustering and Classification”, World Scientific, River Edge, NJ.
  26. S.N Sivanandam, “Introduction to neural networks and MATLAB-6.0”, Tata McGraw-Hill publishing company, 2006.
Index Terms

Computer Science
Information Sciences

Keywords

Adaptive Resonance Theory Simplified fuzzy ARTMAP Competitive learning NFPR-processor Input Generator Preprocessor Separator Discriminator Comparator DNA profiling DNA sequence