Multivariate analysis of flow cytometric data using decision trees.
(2012) Multivariate analysis of flow cytometric data using decision trees. Front Microbiol 3, 114.
Characterization of the response of the host immune system is important in understanding the bidirectional interactions between the host and microbial pathogens. For research on the host site, flow cytometry has become one of the major tools in immunology. Advances in technology and reagents allow now the simultaneous assessment of multiple markers on a single cell level generating multidimensional data sets that require multivariate statistical analysis. We explored the explanatory power of the supervised machine learning method called
doi: 10.3389/fmicb.2012.00114 PMID: 22485112