A deep learning framework for modeling structural features of RNA-binding protein targets

Nucleic Acids Research

Volumn 44, Issue 4, 2015, Pages

  Zhang, Sai ^a   Zhou, Jingtian ^b   Hu, Hailin ^b   Gong, Haipeng ^a   Chen, Ligong ^b   Cheng, Chao ^c   Zeng, Jianyang ^a  

^a TSINGHUA UNIVERSITY   (China)

^b Tsinghua University   (China)

^c DARTMOUTH MEDICAL SCHOOL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

POLYPYRIMIDINE TRACT BINDING PROTEIN; RNA BINDING PROTEIN; MESSENGER RNA;

ARTICLE; BINDING SITE; DATA PROCESSING; INTERNAL RIBOSOME ENTRY SITE; MACHINE LEARNING; PREDICTION; PRIORITY JOURNAL; PROTEIN MOTIF; PROTEIN RNA BINDING; RNA SEQUENCE; RNA STRUCTURE; STATISTICAL ANALYSIS; STATISTICAL MODEL; BIOLOGY; CHEMISTRY; CONFORMATION; GENE EXPRESSION REGULATION; GENETICS; METABOLISM; RIBOSOME; RNA PROCESSING;

BINDING SITES; COMPUTATIONAL BIOLOGY; GENE EXPRESSION REGULATION; NUCLEIC ACID CONFORMATION; POLYPYRIMIDINE TRACT-BINDING PROTEIN; RIBOSOMES; RNA PROCESSING, POST-TRANSCRIPTIONAL; RNA, MESSENGER; RNA-BINDING PROTEINS;

EID: 84960503750     PISSN: 03051048     EISSN: 13624962     Source Type: Journal    
DOI: 10.1093/nar/gkv1025     Document Type: Article

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