gEM/GANN: A multivariate computational strategy for auto‐characterizing relationships between cellular and clinical phenotypes and predicting disease progression time using high‐dimensional flow cytometry data

Publisher： John Wiley & Sons Inc

E-ISSN： 1552-4930|87|7|616-623

ISSN： 1552-4922

Source： CYTOMETRY, Vol.87, Iss.7, 2015-07, pp. : 616-623

Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.

Previous Menu Next

Abstract

Related content

Computational prediction of manually gated rare cells in flow cytometry data

By  

CYTOMETRY, Vol. 87, Iss. 7, 2015-07 ,pp. : 594-602

John Wiley & Sons Inc

Access to resources Recommend Favorite

FlowSOM: Using self‐organizing maps for visualization and interpretation of cytometry data

By  

CYTOMETRY, Vol. 87, Iss. 7, 2015-07 ,pp. : 636-645

John Wiley & Sons Inc

Access to resources Recommend Favorite

State‐of‐the‐Art in the Computational Analysis of Cytometry Data

By  

CYTOMETRY, Vol. 87, Iss. 7, 2015-07 ,pp. : 591-593

John Wiley & Sons Inc

Access to resources Recommend Favorite

Time‐domain microfluidic fluorescence lifetime flow cytometry for high‐throughput Förster resonance energy transfer screening

By  

CYTOMETRY, Vol. 87, Iss. 2, 2015-02 ,pp. : 104-118

John Wiley & Sons Inc

Access to resources Recommend Favorite

Permutation tests for phylogenetic comparative analyses of high‐dimensional shape data: What you shuffle matters

By  

EVOLUTION, Vol. 69, Iss. 3, 2015-03 ,pp. : 823-829

John Wiley & Sons Inc

Access to resources Recommend Favorite