A deep recurrent neural network discovers complex biological rules to decipher RNA protein-coding potential

Nucleic Acids Research

Volumn 46, Issue 16, 2018, Pages 8105-8113

  Hill, Steven T ^a,c   Kuintzle, Rachael ^b,d   Teegarden, Amy ^b   Merrill, Erich ^a   Danaee, Padideh ^a   Hendrix, David A ^a,b  

^a Oregon State University   (United States)

^b OREGON STATE UNIVERSITY   (United States)

^c NEW YORK GENOME CENTER   (United States)

^d CALIFORNIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADENINE; CYTOSINE; GUANINE; LONG UNTRANSLATED RNA; MESSENGER RNA; PARATHYROID HORMONE; PROTEIN CODING RNA; RNA; TRANSCRIPTOME; TUMOR ANTIGEN; UNCLASSIFIED DRUG; URACIL;

3' UNTRANSLATED REGION; 5' UNTRANSLATED REGION; ACCURACY; ARTICLE; ARTIFICIAL NEURAL NETWORK; CLASSIFIER; CODON; CONTROLLED STUDY; DEEP LEARNING; DEEP RECURRENT NEURAL NETWORK; DIAGNOSTIC TEST ACCURACY STUDY; GATED RECURRENT UNIT NETWORK; GENETIC TRANSCRIPTION; HUMAN; MOUSE; MUTATIONAL ANALYSIS; NONHUMAN; POINT MUTATION; PREDICTION; PRIORITY JOURNAL; PROTEIN ANALYSIS; RNA PROTEIN CODING POTENTIAL; RNA SEQUENCE; SCORING SYSTEM; SENSITIVITY AND SPECIFICITY; START CODON; STOP CODON; SUPPORT VECTOR MACHINE; TRANSLATION INDICATING CODON; VALIDATION STUDY; BIOLOGY; GENETICS; MACHINE LEARNING; NUCLEOTIDE SEQUENCE; OPEN READING FRAME; PROCEDURES; PROTEIN SYNTHESIS; REPRODUCIBILITY; SEQUENCE ANALYSIS;

BASE SEQUENCE; COMPUTATIONAL BIOLOGY; HUMANS; MACHINE LEARNING; NEURAL NETWORKS (COMPUTER); OPEN READING FRAMES; PROTEIN BIOSYNTHESIS; REPRODUCIBILITY OF RESULTS; RNA, LONG NONCODING; RNA, MESSENGER; SEQUENCE ANALYSIS, RNA;

EID: 85057336960     PISSN: 03051048     EISSN: 13624962     Source Type: Journal    
DOI: 10.1093/nar/gky567     Document Type: Article

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