Data Mining for Bioinformatics — Microarray Data

  • T.V. Prasad
  • S.I. Ahson


Data could be of any form, symbolic or non-symbolic, continuous or discrete, spatial or non-spatial, it should be understood that whenever the data store becomes voluminous, it requires efficient algorithms to mine out required data as well as provide methods to answer various queries. Though the data analysis techniques are useful in almost all disciplines of study, greater emphasis is given in the area of bioinformatics for mining microarray gene expression data as well as gene sequence data. Considerable work is being done in preparation of protein arrays and corresponding visualization techniques.


Support Vector Machine Microarray Gene Expression Data Principal Component Anal Bioin Formatics Stance Measure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Capital Publishing Company 2009

Authors and Affiliations

  • T.V. Prasad
    • 1
  • S.I. Ahson
    • 2
  1. 1.Dept. of Computer Science & EngineeringLingaya’s Institute of Management & TechnologyFaridabad
  2. 2.Department of Computer ScienceJamia Millia IslamiaNew Delhi

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