Prediction of off-target activities for the end-to-end design of CRISPR guide RNAs

Nature Biomedical Engineering

Volumn 2, Issue 1, 2018, Pages 38-47

  Listgarten, Jennifer ^a   Weinstein, Michael ^b,c   Kleinstiver, Benjamin P ^d,e   Sousa, Alexander A ^d   Joung, J Keith ^d,e   Crawford, Jake ^a   Gao, Kevin ^a   Hoang, Luong ^a   Elibol, Melih ^a   Doench, John G ^f   Fusi, Nicolo ^a  

^a MICROSOFT RESEARCH   (United Kingdom)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c Zymoresearch   (United States)

^d MASSACHUSETTS GENERAL HOSPITAL   (United States)

^e HARVARD MEDICAL SCHOOL   (United States)

^f BROAD INSTITUTE OF MIT AND HARVARD   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACTIVITY PREDICTIONS; CLOUD-BASED; COMPUTATIONAL DEMANDS; END TO END; END-TO-END DESIGN; EVALUATION METHODS; LARGE-SCALES; MACHINE LEARNING MODELS; PRACTICAL USE; TARGET ACTIVITY;

FORECASTING;

CD33 ANTIGEN; CRISPR-CAS SYSTEM GUIDE RNA; NUCLEOTIDE; PENICILLIN DERIVATIVE; STREPTOMYCIN;

ARTICLE; BINDING AFFINITY; CELL AGGREGATION; CELL VIABILITY; CHROMATIN; COMPUTER MODEL; CONTROLLED STUDY; CRISPR-CAS9 SYSTEM; DNA METHYLATION; DRUG DESIGN; END TO END DESIGN; ENTROPY; GENE EDITING; GENE SEQUENCE; HEALTH CARE ACCESS; HUMAN; HUMAN CELL; IN VITRO STUDY; IN VIVO STUDY; K-562 CELL LINE; LINEAR REGRESSION ANALYSIS; MACHINE LEARNING; MAGNITUDE ESTIMATION METHOD; MISMATCH REPAIR; OFF-TARGET EFFECT; PANC-1 CELL LINE; PROBABILITY; RESTRICTION FRAGMENT LENGTH POLYMORPHISM; T-47D CELL LINE; U2OS CELL LINE;

EID: 85040314117     PISSN: None     EISSN: 2157846X     Source Type: Journal    
DOI: 10.1038/s41551-017-0178-6     Document Type: Article

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