An introduction to back propagation learning and its application in classification of genome data sequence

Medha J. Patel, Devarshi Mehta, Patrick Paterson, Rakesh Rawal

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

The gene classification problem is still active area of research because of the attributes of the genome data, high dimensionality and small sample size. Furthermore, the underlying data distribution is also unknown, so nonparametric methods must be used to solve such problems. Learning techniques are efficient in solving complex biological problems due to characteristics such as robustness, fault tolerances, adaptive learning and massively parallel analysis capabilities, and for a biological system it may be employed as tool for data-driven discovery. In this paper, some concepts related to cognition by examples are discussed.Aclassification technique is proposed in which DNA sequence is analyzed on the basis of sequence characteristics near breakpoint that occur in leukemia. The training dataset is built for supervised classifier and on the basis of that back propagation learning classifier is employed on hypothetical data. Our intension is to employ such techniques for further analysis and research in this domain. The future scope and investigation is also suggested.

Original languageEnglish
Title of host publication2nd International Conference on Soft Computing for Problem Solving, SocProS 2012, Proceedings
EditorsB.V. Babu, Atulya Nagar, Jagdish Chand Bansal, Millie Pant, Kusum Deep, Kanad Ray, Umesh Gupta
PublisherSpringer-Verlag
Pages609-615
Number of pages7
ISBN (Electronic)9788132216018
DOIs
StatePublished - 2014
Event2nd International Conference on Soft Computing for Problem Solving, SocProS 2012 - Jaipur, India
Duration: Dec 28 2012Dec 30 2012

Publication series

NameAdvances in Intelligent Systems and Computing
Volume236
ISSN (Print)2194-5357

Conference

Conference2nd International Conference on Soft Computing for Problem Solving, SocProS 2012
CountryIndia
CityJaipur
Period12/28/1212/30/12

Keywords

  • Artificial neural network
  • Cancer classification
  • Supervised classifier

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  • Cite this

    Patel, M. J., Mehta, D., Paterson, P., & Rawal, R. (2014). An introduction to back propagation learning and its application in classification of genome data sequence. In B. V. Babu, A. Nagar, J. C. Bansal, M. Pant, K. Deep, K. Ray, & U. Gupta (Eds.), 2nd International Conference on Soft Computing for Problem Solving, SocProS 2012, Proceedings (pp. 609-615). (Advances in Intelligent Systems and Computing; Vol. 236). Springer-Verlag. https://doi.org/10.1007/978-81-322-1602-5_65