Article Abstract

	Title:	A rich analytical environment for flow cytometry experimental results
	Author:	Janet Siebert, Krzysztof J. Cios, M. Karen Newell
	Address:	Department of Computer Science and Engineering, University of Colorado at Denver and Health Sciences Center, Campus Box 109, P.O. Box 173364, Denver, CO 80217 3364, USA. ' Department of Computer Science and Engineering, University of Colorado at Denver and Health Sciences Center, Campus Box 109, P.O. Box 173364, Denver, CO 80217-3364, USA; Department of Computer Science, University of Colorado at Boulder; Department of Preventive Medicine & Biometrics (School of Medicine), University of Colorado at Denver, Denver, CO, USA. ' University of Colorado at Colorado Springs, CU Institute of Bioenergetics, 1420 Austin Bluffs Parkway, Science Building Room 142, Colorado Springs, CO. 80918, USA
	Journal:	International Journal of Bioinformatics Research and Applications 2006 - Vol. 2, No.1  pp. 52 - 62
	Abstract:	Existing analysis tools for flow cytometry data offer specialised but limited functionality. This work presents advantages of combining the cytometer's data with sample-specific information. Data is loaded into a relational database, where the analyst can query based on sample characteristics such as species, gender, diet type or sample stain type.
	Keywords:	flow cytometry; immunology; data analysis; data mining; knowledge discovery; bioinformatics; relational database.
	DOI:	10.1504/IJBRA.2006.009193
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