Bayesian prediction of tissue-regulated splicing using RNA sequence and cellular context | Zendy

Hui Xiong | Zendy; Yoseph Barash | Zendy; Brendan J. Frey | Zendy

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Bayesian prediction of tissue-regulated splicing using RNA sequence and cellular context

Author(s) -

Hui Xiong,

Yoseph Barash,

Brendan J. Frey

Publication year - 2011

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btr444

Subject(s) - rna splicing , source code , context (archaeology) , alternative splicing , feature (linguistics) , computational biology , exon , computer science , inference , gibbs sampling , bayesian probability , biology , gene , rna , artificial intelligence , genetics , operating system , paleontology , linguistics , philosophy

Alternative splicing is a major contributor to cellular diversity in mammalian tissues and relates to many human diseases. An important goal in understanding this phenomenon is to infer a 'splicing code' that predicts how splicing is regulated in different cell types by features derived from RNA, DNA and epigenetic modifiers.

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