Identification of active transcriptional regulatory elements from GRO-seq data

Nature Methods

Volumn 12, Issue 5, 2015, Pages 433-438

  Danko, Charles G ^a,b   Hyland, Stephanie L ^c   Core, Leighton J ^a,g   Martins, Andre L ^a   Waters, Colin T ^a,g,h   Lee, Hyung Won ^a   Cheung, Vivian G ^d,e   Kraus, W Lee ^f   Lis, John T ^a   Siepel, Adam ^b,g,i  

^a Cornell University ^*  (United States)

^b Program on Infrastructure Policy   (United States)

^c Tri Institutional Training Program in Computational Biology and Medicine   (United States)

^d UNIVERSITY OF MICHIGAN   (United States)

^e HOWARD HUGHES MEDICAL INSTITUTE   (United States)

^f UNIVERSITY OF TEXAS AT DALLAS   (United States)

^g UNIVERSITY OF CONNECTICUT   (United States)

^h HARVARD MEDICAL SCHOOL   (United States)

ⁱ Simons Center for Quantitative Biology   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

HISTONE 3 LYSINE 27; HISTONE H3; TRANSCRIPTION FACTOR; UNCLASSIFIED DRUG; HISTONE;

ACETYLATION; ARTICLE; CASE REPORT; CELLS BY BODY ANATOMY; CONTROLLED STUDY; DISCRIMINATIVE REGULATORY ELEMENT DETECTION; DNA POLYMORPHISM; DNA SEQUENCE; FALSE NEGATIVE RESULT; FOLLOW UP; GENE EXPRESSION; GENETIC ASSOCIATION; GLOBAL RUN ON AND SEQUENCING; HUMAN; HUMAN CELL; MACHINE LEARNING; PRIORITY JOURNAL; PROTEIN BINDING; QUANTITATIVE TRAIT LOCUS; REGULATORY SEQUENCE; RNA SYNTHESIS; SEQUENCE ANALYSIS; SUPPORT VECTOR MACHINE; TRANSCRIPTIONAL REGULATORY ELEMENT; ARTIFICIAL INTELLIGENCE; CELL LINE; COMPUTER PROGRAM; GENE EXPRESSION REGULATION; GENETICS; K562 CELL LINE; PHYSIOLOGY; SINGLE NUCLEOTIDE POLYMORPHISM;

ARTIFICIAL INTELLIGENCE; CELL LINE; GENE EXPRESSION REGULATION; GENOME-WIDE ASSOCIATION STUDY; HISTONES; HUMANS; K562 CELLS; POLYMORPHISM, SINGLE NUCLEOTIDE; QUANTITATIVE TRAIT LOCI; REGULATORY ELEMENTS, TRANSCRIPTIONAL; SOFTWARE;

EID: 84928927316     PISSN: 15487091     EISSN: 15487105     Source Type: Journal    
DOI: 10.1038/nmeth.3329     Document Type: Article

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