Genome-wide prediction of cis-regulatory regions using supervised deep learning methods

BMC Bioinformatics

Volumn 19, Issue 1, 2018, Pages

  Li, Yifeng ^a,b   Shi, Wenqiang ^a   Wasserman, Wyeth W ^a  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^b NATIONAL RESEARCH COUNCIL CANADA   (Canada)

Author keywords

cis regulatory region; Deep learning; Enhancer; Promoter

Indexed keywords

CELL CULTURE; DNA; DNA SEQUENCES; MAMMALS; THROUGHPUT; TRANSCRIPTION;

ENHANCER; FUNCTIONAL ANNOTATION; HIGH-THROUGHPUT SEQUENCING; MACHINE LEARNING TECHNOLOGY; PREDICTIVE PERFORMANCE; PROMOTER; PROTEIN CODING REGIONS; REGULATORY REGIONS;

DEEP LEARNING;

ARTICLE; CANCER MODEL; CELL LINE; CONTROLLED STUDY; ENHANCER REGION; FUNCTIONAL GENOMICS; HIGH THROUGHPUT SEQUENCING; HUMAN; HUMAN CELL; HUMAN EXPERIMENT; HUMAN GENOME; MACHINE LEARNING; MAMMAL; NERVOUS SYSTEM; NONHUMAN; PREDICTION; PROMOTER REGION; ARTIFICIAL NEURAL NETWORK; GENE EXPRESSION REGULATION; GENETICS; GENOMICS; PROCEDURES; REGULATORY SEQUENCE; STANDARDS;

DEEP LEARNING; GENE EXPRESSION REGULATION; GENOMICS; HUMANS; MACHINE LEARNING; NEURAL NETWORKS (COMPUTER); REGULATORY SEQUENCES, NUCLEIC ACID;

EID: 85047942208     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/s12859-018-2187-1     Document Type: Article

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