Advertisement

Neural Networks – A Case Study in Gene Identification

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 247)

Abstract

Gene prediction has been an interesting area of research in Bioinformatics. Many of the recent gene identification methods adopt different approaches which are more robust when dealing with uncertainty and ambiguity. In this paper details of Artificial Neural Networks and using them in study and analysis of Biological data are discussed. The types of neural networks in the area of bioinformatics are listed. The AI technique of simulated annealing is applied. Learning mechanism and evolution of neural networks in the field of bioinformatics are also listed.

Keywords

Gene Prediction Model Artificial Neural Network GRAIL System 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Campbell, A.M., Hyer, L.J.: Discovering Genomics, Proteomics and Bioinformatics. Pearson Education (2004)Google Scholar
  2. 2.
    Role of 5‘- and 3‘- untranslated regions of mRNAs in human diseases Sangeeta Chatterjee and Jayanta K. Pal, University of Pune, Pune 411007. India Biol. Cell 101, 251–262 (2009) (Printed in Great Britain), doi:10.1042/BC20080104Google Scholar
  3. 3.
    Family-based Homology Detection via Pairwise Sequence Comparison, William Noble Grundy, department of Computer Science and Engineering, University of California, San DiegoGoogle Scholar
  4. 4.
    Gene Prediction with a Hidden Markov Model, Mario Stanke, University of Greifswald, GermanyGoogle Scholar
  5. 5.
    Enhancements to Hidden Markov Models for GeneFindings, Tomas Vinar, University of Waterloo, CanadaGoogle Scholar
  6. 6.
    Wu, C.H., McLarty, J.W.: Neural Networks and Genome Informatics, 1st edn. Methods in computational Biology and Biochemistry, vol. 1. Elsevier (2000)Google Scholar
  7. 7.
    Haykin, S.: Neural Networks:A comprehensive Foundation Pearson Education (2002)Google Scholar
  8. 8.
    Wu, C.H., McLarty, J.W.: Neural Networks and Genome Informatics, 1st edn. Methods in computational Biology and Biochemistry, vol. 1. Elsevier (2000)Google Scholar
  9. 9.
    Uberacher, E.C., Xu, Y., Mural, R.J.: Discovering and understanding genes in human DNA sequence using GRAIL. Methods Enzymol. 266, 259–281 (1996)CrossRefGoogle Scholar
  10. 10.
    Molecular design and molecular docking (Rosin et al., 1997; Yang, Kao, 2000; Oshiro et al., 1995; Clark and Westhead, 1996; Venkata subramanian et al., 1994; Deaven and Ho,1995; Jones et al., 1995; Jones et al., 1999; cGarrah and Judson, 1993; Hou et al., 1999; Hatzigeorgiou and Reckzo, 2004) Google Scholar
  11. 11.
    Fogel, G.B., Chellapilla, K., Corne, D.W.: Identification of coding regions in DNA sequences using evolved neural networks, pp. 195–218. Morgan Kaufmann (2002)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Padmasri Dr. BVRICEVishnupurIndia
  2. 2.Department of ITS.R.K.R. Engineering CollegeChinamiramIndia

Personalised recommendations