UNIT 10.13 The Application of Data Mining to Flow Cytometry

  1. Andy N.D. Nguyen

Published Online: 1 MAY 2002

DOI: 10.1002/0471142956.cy1013s20

Current Protocols in Cytometry

Current Protocols in Cytometry

How to Cite

Nguyen, A. N. 2002. The Application of Data Mining to Flow Cytometry. Current Protocols in Cytometry. 20:10.13:10.13.1–10.13.6.

Author Information

  1. University of Texas, Houston, Texas

Publication History

  1. Published Online: 1 MAY 2002
  2. Published Print: APR 2002


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-mining 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.