Computational exploratory analysis of high-dimensional Flow Cytometry data for diagnosis and biomarker discovery
Flow Cytometry (FCM) is widely used to investigate and diagnose human disease. Although high-throughput systems allow rapid data collection from large cohorts, manual data analysis can take months. Moreover, identification of cell populations can be subjective, and analysts rarely examine the entire...
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| Language: | English |
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University of British Columbia
2012
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| Online Access: | http://hdl.handle.net/2429/43669 |