Single cells make big data: New challenges and opportunities in transcriptomics

Current Opinion in Systems Biology

Volumn 4, Issue , 2017, Pages 85-91

  Angerer, Philipp ^a   Simon, Lukas ^a   Tritschler, Sophie ^a   Wolf, F Alexander ^a   Fischer, David ^a   Theis, Fabian J ^a,b  

^a INSTITUTE OF EPIDEMIOLOGY   (Germany)

^b TECHNICAL UNIVERSITY OF MUNICH   (Germany)

Author keywords

Big data; Machine learning; Single cell RNA seq; Single cell transcriptomics

Indexed keywords

MESSENGER RNA; TRANSCRIPTOME;

CANCER CELL; CELL COUNT; CELL HETEROGENEITY; CELLS BY BODY ANATOMY; CLASSIFICATION; CYTOLOGY; DATA ANALYSIS; GENE CONTROL; GENE EXPRESSION; HEMATOPOIETIC STEM CELL; HUMAN; MACHINE LEARNING; MICROARRAY ANALYSIS; MOLECULAR GENETICS; NONHUMAN; PRECANCER; REVERSE TRANSCRIPTION POLYMERASE CHAIN REACTION; REVIEW; RNA PROBE; RNA SEQUENCE; SINGLE CELL TRANSCRIPTOMICS; STATISTICAL ANALYSIS; TRANSCRIPTOMICS;

EID: 85041430720     PISSN: None     EISSN: 24523100     Source Type: Journal    
DOI: 10.1016/j.coisb.2017.07.004     Document Type: Review

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