Molecular identification using flow cytometry histograms and information theory.

Q. Zeng, A. J. Young, A. Boxwala, J. Rawn, W. Long, M. Wand, M. Salganik, E. L. Milford, S. J. Mentzer, R. A. Greenes

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Flow cytometry is a common technique for quantitatively measuring the expression of individual molecules on cells. The molecular expression is represented by a frequency histogram of fluorescence intensity. For flow cytometry to be used as a knowledge discovery tool to identify unknown molecules, histogram comparison is a major limitation. Many traditional comparison methods do not provide adequate assessment of histogram similarity and molecular relatedness. We have explored a new approach applying information theory to histogram comparison, and tested it with histograms from 14 antibodies over 3 cell types. The information theory approach was able to improve over traditional methods by recognizing various non-random correlations between histograms in addition to similarity and providing a quantitative assessment of similarity beyond hypothesis testing of identity.

Original languageEnglish (US)
Pages (from-to)776-780
Number of pages5
JournalProceedings / AMIA ... Annual Symposium. AMIA Symposium
StatePublished - 2001
Externally publishedYes

ASJC Scopus subject areas

  • General Medicine

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