Label-free cell cycle analysis for high-throughput imaging flow cytometry

Nature Communications

Volumn 7, Issue , 2016, Pages

  Blasi, Thomas ^a,b,c   Hennig, Holger ^a   Summers, Huw D ^d   Theis, Fabian J ^b,c   Cerveira, Joana ^e   Patterson, James O ^e   Davies, Derek ^e   Filby, Andrew ^f   Carpenter, Anne E ^a   Rees, Paul ^a,d  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b INSTITUTE OF EPIDEMIOLOGY   (Germany)

^c TECHNICAL UNIVERSITY OF MUNICH   (Germany)

^d SWANSEA UNIVERSITY   (United Kingdom)

^e THE FRANCIS CRICK INSTITUTE   (United Kingdom)

^f NEWCASTLE UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

FLUORESCENT DYE; FUNGAL DNA; DNA;

CELL ORGANELLE; DNA; FLOW CYTOMETRY; MACHINE LEARNING; MORPHOLOGY;

ARTICLE; CONTROLLED STUDY; DNA CONTENT; FLOW CYTOMETRY; HIGH THROUGHPUT SCREENING; MITOSIS; MOLECULAR IMAGING; MONITORING; NONHUMAN; SCHIZOSACCHAROMYCES; SINGLE CELL ANALYSIS; SUPERVISED MACHINE LEARNING; CELL CYCLE; GENETICS; HUMAN; IMAGE PROCESSING; JURKAT CELL LINE; MACHINE LEARNING; PHYSIOLOGY; PROCEDURES;

MAMMALIA; SCHIZOSACCHAROMYCETACEAE;

CELL CYCLE; DNA; FLOW CYTOMETRY; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; JURKAT CELLS; MACHINE LEARNING; SCHIZOSACCHAROMYCES;

EID: 84953896921     PISSN: None     EISSN: 20411723     Source Type: Journal    
DOI: 10.1038/ncomms10256     Document Type: Article

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