Title |
RNAmotifs: prediction of multivalent RNA motifs that control alternative splicing
|
---|---|
Published in |
Genome Biology, January 2014
|
DOI | 10.1186/gb-2014-15-1-r20 |
Pubmed ID | |
Authors |
Matteo Cereda, Uberto Pozzoli, Gregor Rot, Peter Juvan, Anthony Schweitzer, Tyson Clark, Jernej Ule |
Abstract |
RNA-binding proteins (RBPs) regulate splicing according to position-dependent principles, which can be exploited for analysis of regulatory motifs. Here we present RNAmotifs, a method that evaluates the sequence around differentially regulated alternative exons to identify clusters of short and degenerate sequences, referred to as multivalent RNA motifs. We show that diverse RBPs share basic positional principles, but differ in their propensity to enhance or repress exon inclusion. We assess exons differentially spliced between brain and heart, identifying known and new regulatory motifs, and predict the expression pattern of RBPs that bind these motifs. RNAmotifs is available at https://bitbucket.org/rogrro/rna_motifs. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United Kingdom | 2 | 22% |
Australia | 1 | 11% |
Singapore | 1 | 11% |
Canada | 1 | 11% |
United States | 1 | 11% |
India | 1 | 11% |
France | 1 | 11% |
Unknown | 1 | 11% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 5 | 56% |
Scientists | 3 | 33% |
Science communicators (journalists, bloggers, editors) | 1 | 11% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Sweden | 2 | 1% |
Germany | 1 | <1% |
Netherlands | 1 | <1% |
Italy | 1 | <1% |
United Kingdom | 1 | <1% |
Spain | 1 | <1% |
United States | 1 | <1% |
Unknown | 143 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 49 | 32% |
Researcher | 36 | 24% |
Student > Master | 9 | 6% |
Professor | 9 | 6% |
Student > Bachelor | 9 | 6% |
Other | 17 | 11% |
Unknown | 22 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 67 | 44% |
Biochemistry, Genetics and Molecular Biology | 35 | 23% |
Computer Science | 9 | 6% |
Engineering | 5 | 3% |
Medicine and Dentistry | 4 | 3% |
Other | 6 | 4% |
Unknown | 25 | 17% |