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Biclustering and Feature Selection Techniques in Bioinformatics

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 6411))

Abstract

The paper describes several data mining techniques, developed to solve problems which are faced by biologists in Bioinformatics.Several biclustering algorithms which perform clustering on the two dimensions simultaneously are described. Other techniques described in this paper include feature selection methods which help in reducing noise and improving the performance of the classification model.

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© 2012 Springer-Verlag Berlin Heidelberg

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Desai, B., Andhale, P., Rege, M., Yu, Q. (2012). Biclustering and Feature Selection Techniques in Bioinformatics. In: Kannan, R., Andres, F. (eds) Data Engineering and Management. ICDEM 2010. Lecture Notes in Computer Science, vol 6411. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27872-3_42

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  • DOI: https://doi.org/10.1007/978-3-642-27872-3_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-27871-6

  • Online ISBN: 978-3-642-27872-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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