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20231222175832.0 |
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231222s2001 xx ||||| 00| ||eng c |
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|a (DE-627)NLM117123994
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|a (NLM)11825291
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|a DE-627
|b ger
|c DE-627
|e rakwb
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|a eng
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| 100 |
1 |
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|a Zeng, Q
|e verfasserin
|4 aut
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| 245 |
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|a Molecular identification using flow cytometry histograms and information theory
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|c 2001
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|a Text
|b txt
|2 rdacontent
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|a ohne Hilfsmittel zu benutzen
|b n
|2 rdamedia
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|a Band
|b nc
|2 rdacarrier
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|a Date Completed 24.05.2002
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|a Date Revised 13.11.2018
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|a published: Print
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|a Citation Status MEDLINE
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|a 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
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|a Journal Article
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|a Young, A J
|e verfasserin
|4 aut
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|a Boxwala, A
|e verfasserin
|4 aut
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|a Rawn, J
|e verfasserin
|4 aut
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| 700 |
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|a Long, W
|e verfasserin
|4 aut
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| 700 |
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|a Wand, M
|e verfasserin
|4 aut
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| 700 |
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|a Salganik, M
|e verfasserin
|4 aut
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| 700 |
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|a Milford, E L
|e verfasserin
|4 aut
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| 700 |
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|a Mentzer, S J
|e verfasserin
|4 aut
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| 700 |
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|a Greenes, R A
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t Proceedings. AMIA Symposium
|d 1998
|g (2001) vom: 11., Seite 776-80
|w (DE-627)NLM098642928
|x 1531-605X
|7 nnns
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| 773 |
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|g year:2001
|g day:11
|g pages:776-80
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|a AR
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|j 2001
|b 11
|h 776-80
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