Competitive SWIFT cluster templates enhance detection of aging changes

Cytometry Part A

Volumn 89, Issue 1, 2016, Pages 59-70

  Rebhahn, Jonathan A ^a   Roumanes, David R ^a   Qi, Yilin ^a   Khan, Atif ^b   Thakar, Juilee ^b   Rosenberg, Alex ^b   Lee, F Eun Hyung ^c   Quataert, Sally A ^a   Sharma, Gaurav ^b,d   Mosmann, Tim R ^a,b  

^a UNIVERSITY OF ROCHESTER MEDICAL CENTER   (United States)

^b UNIVERSITY OF ROCHESTER   (United States)

^c EMORY UNIVERSITY SCHOOL OF MEDICINE   (United States)

^d University of Rochester   (United States)

Author keywords

Automated analysis; Competitive clustering; EM algorithm; Flow cytometry; Immunophenotyping; Sample comparison; SWIFT; Template

Indexed keywords

BIOLOGICAL MARKER;

ADULT; AGED; AGING; ALGORITHM; BIOLOGY; CLUSTER ANALYSIS; CYTOLOGY; FEMALE; FLOW CYTOMETRY; HUMAN; IMMUNOLOGY; IMMUNOPHENOTYPING; MALE; MIDDLE AGED; MONONUCLEAR CELL; PROCEDURES; SEX DIFFERENCE; STATISTICAL ANALYSIS; VERY ELDERLY; YOUNG ADULT;

ADULT; AGED; AGED, 80 AND OVER; AGING; ALGORITHMS; BIOMARKERS; CLUSTER ANALYSIS; COMPUTATIONAL BIOLOGY; DATA INTERPRETATION, STATISTICAL; FEMALE; FLOW CYTOMETRY; HUMANS; IMMUNOPHENOTYPING; LEUKOCYTES, MONONUCLEAR; MALE; MIDDLE AGED; SEX FACTORS; YOUNG ADULT;

EID: 84983094027     PISSN: 15524922     EISSN: 15524930     Source Type: Journal    
DOI: 10.1002/cyto.a.22740     Document Type: Article

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