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Journal of Immunological Methods
|
March 19, 2013
Highly multiplexed quantitation of gene expression on single cells
Maria H Dominguez, Pratip K Chattopadhyay, Steven Ma, et al.
Breast Cancer Research : BCR
|
August 22, 2012
Gene-expression profiling of microdissected breast cancer microvasculature identifies distinct tumor vascular subtypes
François Pepin, Nicholas Bertos, Julie Laferrière, et al.
Cytometry. Part a : the Journal of the International Society for Analytical Cytology
|
April 25, 2015
Identification and visualization of multidimensional antigen-specific T-cell populations in polychromatic cytometry data
Lin Lin, Jacob Frelinger, Wenxin Jiang, et al.
Plos One
|
December 3, 2010
In silico ascription of gene expression differences to tumor and stromal cells in a model to study impact on breast cancer outcome
Simen Myhre, Hayat Mohammed, Trine Tramm, et al.
Breast Cancer Research : BCR
|
October 24, 2006
Gene expression signatures of morphologically normal breast tissue identify basal-like tumors
Greg Finak, Svetlana Sadekova, Francois Pepin, et al.
Cytometry. Part a : the Journal of the International Society for Analytical Cytology
|
January 3, 2014
High-throughput flow cytometry data normalization for clinical trials
Greg Finak, Wenxin Jiang, Kevin Krouse, et al.
Plos Computational Biology
|
August 29, 2014
OpenCyto: an open source infrastructure for scalable, robust, reproducible, and automated, end-to-end flow cytometry data analysis
Greg Finak, Jacob Frelinger, Wenxin Jiang, et al.
Nature Medicine
|
April 29, 2008
Stromal gene expression predicts clinical outcome in breast cancer
Greg Finak, Nicholas Bertos, Francois Pepin, et al.
JCI Insight
|
June 23, 2016
Distinct activation thresholds of human conventional and innate-like memory T cells
Chloe K Slichter, Andrew McDavid, Hannah W Miller, et al.
Patterns (New York, N.Y.)
|
December 24, 2021
New interpretable machine-learning method for single-cell data reveals correlates of clinical response to cancer immunotherapy
Evan Greene, Greg Finak, Leonard A D'Amico, et al.
Page
of 6
Search research articles
Search
Showing results (21-30 of 54) with videos related to
Sort By:
Page
of 6
Journal of Immunological Methods
|
March 19, 2013
Highly multiplexed quantitation of gene expression on single cells
Maria H Dominguez, Pratip K Chattopadhyay, Steven Ma, et al.
Breast Cancer Research : BCR
|
August 22, 2012
Gene-expression profiling of microdissected breast cancer microvasculature identifies distinct tumor vascular subtypes
François Pepin, Nicholas Bertos, Julie Laferrière, et al.
Cytometry. Part a : the Journal of the International Society for Analytical Cytology
|
April 25, 2015
Identification and visualization of multidimensional antigen-specific T-cell populations in polychromatic cytometry data
Lin Lin, Jacob Frelinger, Wenxin Jiang, et al.
Plos One
|
December 3, 2010
In silico ascription of gene expression differences to tumor and stromal cells in a model to study impact on breast cancer outcome
Simen Myhre, Hayat Mohammed, Trine Tramm, et al.
Breast Cancer Research : BCR
|
October 24, 2006
Gene expression signatures of morphologically normal breast tissue identify basal-like tumors
Greg Finak, Svetlana Sadekova, Francois Pepin, et al.
Cytometry. Part a : the Journal of the International Society for Analytical Cytology
|
January 3, 2014
High-throughput flow cytometry data normalization for clinical trials
Greg Finak, Wenxin Jiang, Kevin Krouse, et al.
Plos Computational Biology
|
August 29, 2014
OpenCyto: an open source infrastructure for scalable, robust, reproducible, and automated, end-to-end flow cytometry data analysis
Greg Finak, Jacob Frelinger, Wenxin Jiang, et al.
Nature Medicine
|
April 29, 2008
Stromal gene expression predicts clinical outcome in breast cancer
Greg Finak, Nicholas Bertos, Francois Pepin, et al.
JCI Insight
|
June 23, 2016
Distinct activation thresholds of human conventional and innate-like memory T cells
Chloe K Slichter, Andrew McDavid, Hannah W Miller, et al.
Patterns (New York, N.Y.)
|
December 24, 2021
New interpretable machine-learning method for single-cell data reveals correlates of clinical response to cancer immunotherapy
Evan Greene, Greg Finak, Leonard A D'Amico, et al.
Page
of 6