Prospective identification of hematopoietic lineage choice by deep learning

Nature Methods

Volumn 14, Issue 4, 2017, Pages 403-406

  Buggenthin, Felix ^a   Buettner, Florian ^a,b   Hoppe, Philipp S ^a,c   Endele, Max ^c   Kroiss, Manuel ^a   Strasser, Michael ^a   Schwarzfischer, Michael ^a   Loeffler, Dirk ^a,c   Kokkaliaris, Konstantinos D ^a,c   Hilsenbeck, Oliver ^a,c   Schroeder, Timm ^a,c   Theis, Fabian J ^a,d   Marr, Carsten ^a  

^a INSTITUTE OF EPIDEMIOLOGY   (Germany)

^b EUROPEAN BIOINFORMATICS INSTITUTE   (United Kingdom)

^c ETH ZURICH   (Switzerland)

^d TECHNICAL UNIVERSITY OF MUNICH   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

CD16 ANTIGEN; CD32 ANTIGEN; MOLECULAR MARKER; TRANSCRIPTION FACTOR GATA 1; TRANSCRIPTION FACTOR PU 1; BIOLOGICAL MARKER; ONCOPROTEIN; PROTO-ONCOGENE PROTEIN SPI-1; TRANSACTIVATOR PROTEIN;

ANIMAL CELL; ANIMAL EXPERIMENT; ARTICLE; CELL DIFFERENTIATION; CELL FATE; CELL LINEAGE; CELL MOTION; CELL STRUCTURE; HEMATOPOIETIC STEM CELL; MOUSE; NERVE CELL NETWORK; NONHUMAN; PRIORITY JOURNAL; PROTEIN EXPRESSION; TIME-LAPSE MICROSCOPY; ANIMAL; AREA UNDER THE CURVE; ARTIFICIAL NEURAL NETWORK; CYTOLOGY; GENE TARGETING; GENETICS; IMAGE PROCESSING; MACHINE LEARNING; MALE; METABOLISM; MUTANT MOUSE STRAIN; PHYSIOLOGY; PROCEDURES; TIME LAPSE IMAGING;

ANIMALS; AREA UNDER CURVE; BIOMARKERS; CELL DIFFERENTIATION; CELL LINEAGE; GENE KNOCK-IN TECHNIQUES; HEMATOPOIETIC STEM CELLS; IMAGE PROCESSING, COMPUTER-ASSISTED; MACHINE LEARNING; MALE; MICE, MUTANT STRAINS; NEURAL NETWORKS (COMPUTER); PROTO-ONCOGENE PROTEINS; TIME-LAPSE IMAGING; TRANS-ACTIVATORS;

EID: 85013149570     PISSN: 15487091     EISSN: 15487105     Source Type: Journal    
DOI: 10.1038/nmeth.4182     Document Type: Article

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