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Annals of the Academy of Medicine, Singapore
|
March 17, 2007
Computational immunology--from bench to virtual reality
Cliburn Chan, Thomas B Kepler
Immunological Reviews
|
March 21, 2007
Spatiotemporal programming of a simple inflammatory process
Thomas B Kepler, Cliburn Chan
Biostatistics (Oxford, England)
|
June 5, 2015
Discriminative variable subsets in Bayesian classification with mixture models, with application in flow cytometry studies
Lin Lin, Cliburn Chan, Mike West
Bayesian Analysis
|
May 29, 2026
Coarsened Mixtures of Hierarchical Skew Normal Kernels for Flow and Mass Cytometry Analyses
Shai Gorsky, Cliburn Chan, Li Ma
Bayesian Analysis
|
September 25, 2010
Selection Sampling from Large Data Sets for Targeted Inference in Mixture Modeling
Ioanna Manolopoulou, Cliburn Chan, Mike West
Bayesian Analysis
|
June 1, 2026
A Tree Perspective on Stick-Breaking Models in Covariate-Dependent Mixtures (with Discussion)
Akira Horiguchi, Cliburn Chan, Li Ma
Source Code for Biology and Medicine
|
June 19, 2008
Flow: Statistics, visualization and informatics for flow cytometry
Jacob Frelinger, Thomas B Kepler, Cliburn Chan
Cancer Immunology, Immunotherapy : CII
|
June 22, 2010
Modeling flow cytometry data for cancer vaccine immune monitoring
Jacob Frelinger, Janet Ottinger, Cécile Gouttefangeas, et al.
Trends in Immunology
|
October 21, 2005
Understanding specificity and sensitivity of T-cell recognition
Andrew J T George, Jaroslav Stark, Cliburn Chan
Proceedings. Biological Sciences
|
July 17, 2004
Feedback control of T-cell receptor activation
Cliburn Chan, Jaroslav Stark, Andrew J T George
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Search research articles
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Showing results (1-10 of 118) with videos related to
Sort By:
Page
of 12
Annals of the Academy of Medicine, Singapore
|
March 17, 2007
Computational immunology--from bench to virtual reality
Cliburn Chan, Thomas B Kepler
Immunological Reviews
|
March 21, 2007
Spatiotemporal programming of a simple inflammatory process
Thomas B Kepler, Cliburn Chan
Biostatistics (Oxford, England)
|
June 5, 2015
Discriminative variable subsets in Bayesian classification with mixture models, with application in flow cytometry studies
Lin Lin, Cliburn Chan, Mike West
Bayesian Analysis
|
May 29, 2026
Coarsened Mixtures of Hierarchical Skew Normal Kernels for Flow and Mass Cytometry Analyses
Shai Gorsky, Cliburn Chan, Li Ma
Bayesian Analysis
|
September 25, 2010
Selection Sampling from Large Data Sets for Targeted Inference in Mixture Modeling
Ioanna Manolopoulou, Cliburn Chan, Mike West
Bayesian Analysis
|
June 1, 2026
A Tree Perspective on Stick-Breaking Models in Covariate-Dependent Mixtures (with Discussion)
Akira Horiguchi, Cliburn Chan, Li Ma
Source Code for Biology and Medicine
|
June 19, 2008
Flow: Statistics, visualization and informatics for flow cytometry
Jacob Frelinger, Thomas B Kepler, Cliburn Chan
Cancer Immunology, Immunotherapy : CII
|
June 22, 2010
Modeling flow cytometry data for cancer vaccine immune monitoring
Jacob Frelinger, Janet Ottinger, Cécile Gouttefangeas, et al.
Trends in Immunology
|
October 21, 2005
Understanding specificity and sensitivity of T-cell recognition
Andrew J T George, Jaroslav Stark, Cliburn Chan
Proceedings. Biological Sciences
|
July 17, 2004
Feedback control of T-cell receptor activation
Cliburn Chan, Jaroslav Stark, Andrew J T George
Page
of 12