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Flow Cytometry Data Analysis: Basic Concepts and Statistics

Flow Cytometry Data Analysis: Basic Concepts and Statistics

Flow Cytometry Data Analysis: Basic Concepts and Statistics
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Flow Cytometry Data Analysis: Basic Concepts and Statistics Paperback - 2005

by Watson, James V

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Cambridge University Press, 2005-09-01. Paperback. New. In shrink wrap. Looks like an interesting title!
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Details

  • Title Flow Cytometry Data Analysis: Basic Concepts and Statistics
  • Author Watson, James V
  • Binding Paperback
  • Condition New
  • Pages 300
  • Volumes 1
  • Language ENG
  • Publisher Cambridge University Press
  • Publication date 2005-09-01
  • Illustrated Yes
  • Features Bibliography, Illustrated, Index
  • Bookseller's Inventory # Q-0521019702
  • ISBN 9780521019705 / 0521019702
  • Weight 0.97 lbs (0.44 kg)
  • Dimensions 9 x 6 x 0.67 in (22.86 x 15.24 x 1.70 cm)
  • Category Science
  • Library of Congress subjects Flow cytometry - Statistical methods, Flow cytometry - Mathematics
  • Library of Congress Catalogue Number 2006271291
  • Dewey Decimal Code 616.075
  • Quantity available 1

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From the publisher

This book covers very basic number handling techniques, regression analysis, probability functions, statistical tests and methods of analyzing dynamic processes from flow cytometry data. These are developed for the analysis of not only individual DNA histograms to obtain the proportion of cells in the cell cycle phases, but also time courses of DNA histograms to yield cell cycle kinetic information; overlapping immunofluorescence distributions with confidence limits for the estimated proportions; enzyme kinetic and membrane transport parameters and a brief introduction to multivariate analysis is given. A distinction is made between data handling, for example gating and counting the numbers of cells within that gate, a process commonly regarded as data analysis but which, in reality, is data handling, and data analysis itself which is the means by which information is extracted.

First line

Flow cytometry is now a well established technique in cell biology and is gaining increasing use in clinical medicine.

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