Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk

Nature Genetics

Volumn 50, Issue 8, 2018, Pages 1171-1179

  Zhou, Jian ^a,b   Theesfeld, Chandra L ^a   Yao, Kevin ^b   Chen, Kathleen M ^b   Wong, Aaron K ^b   Troyanskaya, Olga G ^a,b,c  

^a PRINCETON UNIVERSITY   (United States)

^b FLATIRON INSTITUTE   (United States)

^c Princeton University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

RNA POLYMERASE II;

AB INITIO CALCULATION; ARTICLE; COMPUTER MODEL; COMPUTER PREDICTION; DNA SEQUENCE; EXPECTO; GENE EXPRESSION; GENE LOCUS; GENE MUTATION; GENETIC TRAIT; GENOME-WIDE ASSOCIATION STUDY; MUTAGENESIS; PRIORITY JOURNAL; PROMOTER REGION; TISSUE SPECIFICITY; ALGORITHM; BIOLOGICAL MODEL; COMPUTER SIMULATION; GENETIC PREDISPOSITION; GENETICS; HUMAN; MUTATION; PROCEDURES; QUANTITATIVE TRAIT LOCUS; SINGLE NUCLEOTIDE POLYMORPHISM;

ALGORITHMS; COMPUTER SIMULATION; DEEP LEARNING; GENE EXPRESSION; GENETIC PREDISPOSITION TO DISEASE; GENOME-WIDE ASSOCIATION STUDY; HUMANS; MODELS, GENETIC; MUTATION; POLYMORPHISM, SINGLE NUCLEOTIDE; PROMOTER REGIONS, GENETIC; QUANTITATIVE TRAIT LOCI;

EID: 85049967126     PISSN: 10614036     EISSN: 15461718     Source Type: Journal    
DOI: 10.1038/s41588-018-0160-6     Document Type: Article

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