Rationale:
The correct post-transcriptional RNA processing, such as capping, polyadenilation, splicing, export and partially the secondary structure, are finely regulated by RNA-binding proteins. DNA mutations can affect some of these processes, mainly the splicing efficiency and accuracy, by destroying or creating target RNA sequences thereby changing the complex of proteins bound to the pre-mRNA. To predict the effects of mutations at the RNA level, it is necessary to know the RNA sequences recognized by each protein involved in post-transcriptional RNA processing. Unfortunately there is little experimental information on target RNA sequences of RNA-binding proteins because of the difficulty in working with RNA and moreover such experimentally derived target sequences are annotated in a compact form by the score matrices. This formalism is an easy way to describe the target sequences of a certain protein but it overestimates the number of possible recognized sequences because it does not consider nucleotide correlations that are in the different positions within the experimentally assessed sequences.
We carried out an exhaustive hand curated literature search to create a database collecting all the experimentally assessed target RNA sequences that are bound by splicing proteins in humans. We built a web resource, database driven, that within the sequence submitted by a user identifies the exact correspondence with the sequences stored in the database.
SpliceAid gives the results back by an accurate and dynamic graphic representation.
This tool searches the exact motifs versus a database of strictly experimentally assessed target RNA sequences. It is useful for predicting the effect of the DNA mutations at the level of the target sequences of the RNA-binding proteins that determine the pattern of mRNA splicing.

Interpret the results:
It processes the sequence submitted by the user and identifies the exact correspondence with the sequences stored in the database. Such sequences are shown by an accurate graphic representation, that is by histogram in which each target RNA sequence is represented by a coloured bar. A positive score was assigned to the target sequences that facilitate exon definition that is ESE (exonic splicing enhancer) and ISS (intronic splicing silencer) motifs. According to the same criteria we assigned a negative score to the target sequences that facilitate intron definition that is ESS (exonic splicing silencer) and ISE (intronic splicing enhancer) motifs. The bars have variable width and height respectively related to the number of nucleotides of the binding site and to its score (binding affinity). Over each bar there is the label showing the name of the protein predicted to bind moreover overlapping bars are managed shifting the labels and changing the colours. Moving the mouse over the factors name label, a window will appear showing the references that bring to connect (support) that binding sequence with its factor.
The tool keeps the case characters of the submitted sequences so the user can used it to distinguish coding from non coding areas and he will find again it in the results.

Literature revision
All the articles analyzed to build SpliceAid database are available here

Comparisons
A table showing some comparisons among different prediction tools is available here

Print results
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Citation
SpliceAid: a database of experimental RNA target motifs bound by splicing proteins in humans
Piva F, Giulietti M, Nocchi L, Principato G
Bioinformatics. 2009 Mar 4; doi: 10.1093/bioinformatics/btp124
PubMed ID: 19261717

Link
RegRNA A Regulatory RNA Motifs and Elements collection
ESE Finder 3.0
RESCUE-ESE
Splicing Rainbow