Computational flow cytometry: Helping to make sense of high-dimensional immunology data

Nature Reviews Immunology

Volumn 16, Issue 7, 2016, Pages 449-462

  Saeys, Yvan ^a,b   Van Gassen, Sofie ^a,c   Lambrecht, Bart N ^a,b,d  

^a DEPARTMENT OF PLANT SYSTEMS BIOLOGY   (Belgium)

^b GHENT UNIVERSITY   (Belgium)

^c Department of Information Technology ^*  (Belgium)

^d ERASMUS MEDICAL CENTER   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL MARKER;

AUTOFLUORESCENCE; BIOLOGY; CELL MATURATION; FLOW CYTOMETER; FLOW CYTOMETRY; IMMUNOLOGY; MACHINE LEARNING; PRACTICE GUIDELINE; PRIORITY JOURNAL; QUALITY CONTROL; REPRODUCIBILITY; REVIEW; STANDARDIZATION; ANIMAL; HUMAN; IMMUNOLOGICAL TECHNIQUE; PROCEDURES;

ANIMALS; COMPUTATIONAL BIOLOGY; FLOW CYTOMETRY; HUMANS; IMMUNOLOGIC TECHNIQUES;

EID: 84975122314     PISSN: 14741733     EISSN: 14741741     Source Type: Journal    
DOI: 10.1038/nri.2016.56     Document Type: Review

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