Automatic Classification of Cellular Expression by Nonlinear Stochastic Embedding (ACCENSE)

Proceedings of the National Academy of Sciences of the United States of America

Volumn 111, Issue 1, 2014, Pages 202-207

  Shekhar, Karthik ^a,b   Brodin, Petter ^c   Davis, Mark M ^c   Chakraborty, Arup K ^a,b  

^a Massachusetts Institute of Technology Cambridge   (United States)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^c STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

Class discovery; CyTOF; FACS; Immunophenotyping; Machine learning

Indexed keywords

ANIMAL CELL; ARTICLE; AUTOMATIC CLASSIFICATION OF CELLULAR EXPRESSION BY NONLINEAR STOCHASTIC EMBEDDING; CD8+ T LYMPHOCYTE; CELL HETEROGENEITY; CELLULAR PARAMETERS; CONTROLLED STUDY; CYTOMETRY; GERMFREE ANIMAL; MOUSE; NONHUMAN; NONLINEAR SYSTEM; PHENOTYPE; PRIORITY JOURNAL; T LYMPHOCYTE SUBPOPULATION;

CLASS DISCOVERY; CYTOF; FACS; IMMUNOPHENOTYPING; MACHINE LEARNING;

ANIMALS; ARTIFICIAL INTELLIGENCE; AUTOMATION; CD8-POSITIVE T-LYMPHOCYTES; COMPUTER SIMULATION; FLOW CYTOMETRY; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENETIC MARKERS; IMMUNOLOGIC MEMORY; IMMUNOPHENOTYPING; MICE; PHENOTYPE; PROBABILITY; SIGNAL PROCESSING, COMPUTER-ASSISTED; STOCHASTIC PROCESSES; TIME FACTORS;

EID: 84891956083     PISSN: 00278424     EISSN: 10916490     Source Type: Journal    
DOI: 10.1073/pnas.1321405111     Document Type: Article

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