Analysis of Flow Cytometry Data by Matrix Relevance Learning Vector Quantization
Analysis of Flow Cytometry Data by Matrix Relevance Learning Vector Quantization
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United States: Public Library of Science
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Language
English
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Publisher
United States: Public Library of Science
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Contents
Flow cytometry is a widely used technique for the analysis of cell populations in the study and diagnosis of human diseases. It yields large amounts of high-dimensional data, the analysis of which would clearly benefit from efficient computational approaches aiming at automated diagnosis and decision support. This article presents our analysis of f...
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Full title
Analysis of Flow Cytometry Data by Matrix Relevance Learning Vector Quantization
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TN_cdi_plos_journals_1330893356
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_1330893356
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ISSN
1932-6203
E-ISSN
1932-6203
DOI
10.1371/journal.pone.0059401
