Title
Using a neural network with flow cytometry histograms to recognize cell surface protein binding patterns.
Abstract
Flow cytometric systems are being used increasingly in all branches of biological science including medicine. To develop analytic tools for identifying unknown molecules such as the antibodies that recognize different structure in the identical antigens, we explored use of a neural network in flow cytometry data comparison. Peak locations were extracted from flow cytometry histograms and we used the Marquardt backpropagation neural networks to recognize identical or similar binding patterns between antibodies and antigens based on the peak locations. The neural network showed 93.8% to 99.6% correct classification rates for identical or similar molecules. This suggests that the neural network technique can be useful in flow cytometry histogram data analysis.
Year
Venue
Keywords
2002
AMIA 2002 SYMPOSIUM, PROCEEDINGS: BIOMEDICAL INFORMATICS: ONE DISCIPLINE
protein binding,flow cytometry,membrane proteins
Field
DocType
ISSN
Histogram,Plasma protein binding,Flow cytometry,Biology,Pattern recognition,Artificial intelligence,Artificial neural network,Backpropagation,Molecular biology
Conference
1531-605X
Citations 
PageRank 
References 
2
0.43
2
Authors
8
Name
Order
Citations
PageRank
eun young kim17111.21
Qing Zeng254767.98
James Rawn372.10
Matthew Wand420.43
Alan J Young550.87
Edgar Milford661.73
Steven J Mentzer7213.93
Robert Greenes8644106.18