Sensitive and highly resolved identification of RNA-protein interaction sites in PAR-CLIP data

BMC Bioinformatics

Volumn 16, Issue 1, 2015, Pages

  Comoglio, Federico ^a   Sievers, Cem ^a,b,c   Paro, Renato ^a,d  

^a ETH ZURICH   (Switzerland)

^b MASSACHUSETTS GENERAL HOSPITAL   (United States)

^c BROAD INSTITUTE OF MIT AND HARVARD   (United States)

^d UNIVERSITY OF BASEL   (Switzerland)

Author keywords

Bayesian statistics; PAR CLIP; RNA; RNA binding proteins

Indexed keywords

BAYESIAN NETWORKS; BIOCHEMISTRY; PROTEINS; RNA;

ALTERNATIVE ALGORITHMS; BAYESIAN STATISTICS; COMPUTATIONAL FRAMEWORK; NEXT-GENERATION SEQUENCING; PAR-CLIP; PROTEIN-BINDING SITES; RNA-BINDING PROTEIN; RNA-PROTEIN INTERACTIONS;

BINDING SITES;

MICRORNA; RNA; RNA BINDING PROTEIN; TRANSCRIPTOME;

ALGORITHM; BAYES THEOREM; BINDING SITE; CHEMISTRY; HEK293 CELL LINE; HIGH THROUGHPUT SEQUENCING; HUMAN; IMMUNOPRECIPITATION; METABOLISM; PROCEDURES; SEQUENCE ANALYSIS; STATISTICAL MODEL;

ALGORITHMS; BAYES THEOREM; BINDING SITES; HEK293 CELLS; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; IMMUNOPRECIPITATION; MICRORNAS; MODELS, STATISTICAL; RNA; RNA-BINDING PROTEINS; SEQUENCE ANALYSIS, RNA; TRANSCRIPTOME;

EID: 84923917411     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/s12859-015-0470-y     Document Type: Article

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