The Application of Data Mining to Flow Cytometry

Andy N.D. Nguyen1

1 University of Texas, Houston, Texas
Publication Name:  Current Protocols in Cytometry
Unit Number:  Unit 10.13
DOI:  10.1002/0471142956.cy1013s20
Online Posting Date:  May, 2002
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Abstract

Data mining is the process of automating information discovery to detect useful patterns, correlations, and trends. Existing data must be fitted into a representative model from which useful information can be derived through a variety of algorithms. The routine generation of vast amounts of data make flow cytometry a logical target for the application of data mining. This informative unit discusses the steps of the data‚Äźmining process using the immunophenotyping of hematologic neoplasms to demonstrate the application. The author describes several types of algorithms and provides a useful resource list of commercially available tools.

     
 
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Table of Contents

  • Introduction to Data Mining
  • Data Mining and Flow Cytometry
  • The Data‐Mining Process
  • Data‐Mining Algorithms
  • Resources
  • Literature Cited
  • Figures
     
 
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Materials

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Figures

Videos

Literature Cited

Literature Cited
   Adriaans, P. and Zantinge, D. 1996. Data Mining. 1st ed. Addison‐Wesley, Harlow, England.
   Cabena, P., Hadjinian, P., Stadler, R., Verhees, J., and Zanasi, A. 1998. Discovering Data Mining: from Concept to Implementation. 1st ed. Prentice Hall, Inc., Upper Saddle River, N.J.
   Fayad, U., Piatetsky‐Shapiro, G., and Smyth, P. 1996. From data mining to knowledge discovery: An overview. In Advances in Knowledge Discovery and Data Mining (U. Fayad, G. Piatetsky‐Shapiro, P. Smyth, and R. Uthurusamy, eds.) pp. 1‐34. AAAI Press/MIT Press, Menlo Park, Calif.
   McDonald, J.M., Brossette, S., and Mose, S.A. 1998. Pathology information systems: Data mining leads to knowledge discovery. Arch. Pathol. Lab Med. 122:409‐411.
   Parsaye, K. and Chignell, M. 1993. Intelligent Database Tools and Applications. 1st ed. John Wiley & Sons, New York.
   Piatetsky‐Shapiro, G. 1996. An overview of issues in developing industrial data mining and knowledge discovery applications. Proceedings of the Second International Conference on Knowledge Discovery and Data Mining, p 89. AAAI Press/MIT Press, Menlo Park, Calif.
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