Deep learning of genomic variation and regulatory network data

Human Molecular Genetics

Volumn 27, Issue R1, 2018, Pages R63-R71

  Telenti, Amalio ^a   Lippert, Christoph ^b   Chang, Pi Chuan ^c   DePristo, Mark ^c  

^a SCRIPPS RESEARCH INSTITUTE   (United States)

^b MAX DELBRÜCK CENTER FOR MOLECULAR MEDICINE   (Germany)

^c GOOGLE INC   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; DATA ANALYSIS; EXOME; GENE REGULATORY NETWORK; GENETIC VARIATION; GENOME ANALYSIS; GENOMICS; HUMAN; HUMAN GENOME; MACHINE LEARNING; POPULATION GENETICS; PRIORITY JOURNAL; REVIEW; DNA SEQUENCE; GENETICS; HIGH THROUGHPUT SEQUENCING; SOFTWARE; TRENDS;

DEEP LEARNING; EXOME; GENE REGULATORY NETWORKS; GENOME, HUMAN; GENOMICS; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; SEQUENCE ANALYSIS, DNA; SOFTWARE;

EID: 85048632046     PISSN: 09646906     EISSN: 14602083     Source Type: Journal    
DOI: 10.1093/hmg/ddy115     Document Type: Review

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