Modeling flow cytometry data for cancer vaccine immune monitoring

Cancer Immunology, Immunotherapy

Volumn 59, Issue 9, 2010, Pages 1435-1441

  Frelinger, Jacob ^a   Ottinger, Janet ^b   Gouttefangeas, Cécile ^c   Chan, Cliburn ^b  

^a DUKE UNIVERSITY   (United States)

^b DUKE UNIVERSITY MEDICAL CENTER   (United States)

^c UNIVERSITY OF TÜBINGEN   (Germany)

Author keywords

Automation; Flow cytometry; Immune monitoring; Markov chain Monte Carlo; Model based analysis; Standardization

Indexed keywords

CANCER VACCINE; HLA A2 ANTIGEN;

CANCER IMMUNOTHERAPY; CD3+ T LYMPHOCYTE; CD4+ T LYMPHOCYTE; CD8+ T LYMPHOCYTE; FALSE NEGATIVE RESULT; FALSE POSITIVE RESULT; FLOW CYTOMETRY; HUMAN; IMMUNOLOGICAL MONITORING; INTRACELLULAR SIGNALING; MINIMAL RESIDUAL DISEASE; PRIORITY JOURNAL; REGULATORY T LYMPHOCYTE; REVIEW; SENSITIVITY AND SPECIFICITY; STANDARDIZATION; STATISTICAL MODEL;

ANIMALS; CANCER VACCINES; CELL SEPARATION; COMPUTATIONAL BIOLOGY; DIAGNOSIS, COMPUTER-ASSISTED; FLOW CYTOMETRY; HUMANS; MONITORING, IMMUNOLOGIC; SENSITIVITY AND SPECIFICITY; STATISTICS AS TOPIC;

EID: 77955512886     PISSN: 03407004     EISSN: 14320851     Source Type: Journal    
DOI: 10.1007/s00262-010-0883-4     Document Type: Review

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