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Predicts which sequences have exonic splicing enhancer (ESE) activity by statistical analysis of exon-intron and splice site composition. When large data sets of human gene sequences were used, RESCUE-ESE identified 10 predicted ESE motifs. Representatives of all 10 motifs were found to display enhancer activity in vivo, whereas point mutants of these sequences exhibited sharply reduced activity. The motifs identified enable prediction of the splicing phenotypes of exonic mutations in human genes.


A tool for the detection of exonic variants that modulate splicing. SKIPPY allows users to input a set of exonic variants to score them for a number of features (such as changes in splicing regulatory elements) that have been shown to be predictive of known genome variations that cause exon skipping or activation of ectopic splice sites. In this way, variants can be either prioritized for further splicing-based functional analysis or the results can be used as further genomic evidence in cases in which the causative variant is already known.


A support vector machine (SVM) model to predict aberrant splicing because of intronic SNVs (Int-SNVs) at positions from Int-50 to Int-3 (Int-50:Int-3). Following an effect-size analysis of each intronic nucleotide on annotated alternative splicing, we extracted 105 parameters that could affect the strength of the splicing signals. However, we could not generate reliable support vector regression models to predict the percent-splice-in (PSI) scores for normal human tissues. Next, we generated support vector machine (SVM) models using 110 parameters to directly differentiate pathogenic SNVs in the Human Gene Mutation Database and normal SNVs in the dbSNP database, and we obtained models with a sensitivity of 0.800±0.041 (mean and s.d.) and a specificity of 0.849±0.021. Our IntSplice models were more discriminating than SVM models that we generated with Shapiro-Senapathy score and MaxEntScan::score3ss.


A web application for 5′ and 3′ splice site prediction. CRYP-SKIP takes up one or more mutated alleles, each consisting of one exon and flanking intronic sequences, and provides a list of important predictor variables and their values, the overall probability of activating cryptic splice vs exon skipping, and the location and intrinsic strength of predicted cryptic splice sites in the input sequence. These results will facilitate phenotypic prediction of splicing mutations and provide further insights into splicing enhancer and silencer elements and their relative importance for splice-site selection in vivo.


Allows for the identification of putative exonic splicing enhancers (ESEs) and one of its most useful applications is the correct interpretation of the effects of disease-associated point mutations or polymorphisms. The development and refinement of reliable prediction tools for auxiliary splicing elements will have important implications for our ability to accurately identify the exon/intron structures of genes and predict their expression profile, to correctly interpret the effects of point mutations and/or polymorphisms, and to assess phenotypic risk.


Provides computational biology resources that are related to the genome/transcriptome of the model plant Physcomitrella patens (Aphanoregma patens). Cosmoss is a web app that offer both the transcriptome representation (including a BLAST and retrieval service) and splice site prediction of Physcomitrella. The moss Physcomitrella patens is an emerging plant model system due to its high rate of homologous recombination, haploidy, simple body plan, physiological properties as well as phylogenetic position.


A versatile tool with two main functions. First, the user can perform accurate splice-site prediction on a sequence which they input to the tool, with the flexibility of exploring all the putative splice-site locations, their score, corresponding sensitivity and false positive rate values. Second, the user can explore the motifs for the requested location in the input sequence and browse the complete collection of identified motifs for both acceptor and donor splice sites. This tool can both help a user decide whether there is a splice site in the given sequence, and it can also allow the user to identify elements of functional motifs. An additional benefit of a computational exploration approach such as SplicePort is that it can be readily implemented in other genomes.


Artificial neural networks have been combined with a rule based system to predict intron splice sites in the dicot plant Arabidopsis thaliana. A two step prediction scheme, where a global prediction of the coding potential regulates a cutoff level for a local prediction of splice sites, is refined by rules based on splice site confidence values, prediction scores, coding context and distances between potential splice sites. In this approach, the prediction of splice sites mutually affect each other in a non-local manner. The combined approach drastically reduces the large amount of false positive splice sites normally haunting splice site prediction.

SROOGLE / Splicing RegulatiOn Online GraphicaL Engine

Makes splicing signal sequence and scoring data available to the biologist in an integrated, visual, easily interpretable, and user-friendly format. SROOGLE's input consists of the sequence of an exon and flanking introns. The graphic browser output displays the four core splicing signals with scores based on nine different algorithms and highlights sequences belonging to 13 different groups of splicing-regulatory sequences (SRSs). The interface also offers the ability to examine the effect of point mutations at any given position, as well a range of additional metrics and statistical measures regarding each potential signal.

BPS predictor

Quantifies the splicing strength of putative branch point sequences BPSs in a newly defined BPS search region. BPS predictor improves the prediction accuracy of human BPS. The model was tested on two sets of experimentally verified human introns. This tool is based on position-specific scoring matrix (PSSM) method to depict the relative frequencies of each nucleotide at specific position for motif pattern. It was applied to human BPS prediction but can be extended to other species.


An automated bioinformatics pipeline to analyse SNP containing DNA sequences mainly for finding SNPs which cause a change in the splicing pattern. AASsites first determines the position of the SNP. Then the splice pattern between wt and mutant gene sequence using different gene prediction programs are compared. If the location of the SNP is in an exon, ORF analysis and ESE analysis follows. The results are combined and a probability for a change in splicing in the classes "likely", "probable", and "unlikely" is given.


A web application for functional site analysis. SpliceView is based on four main assumptions: each variation of nucleotide composition makes a different contribution to the overall binding free energy of interaction between a functional site and another molecule; nonfunctioning site-like regions (pseudosites) are absent or rare in genomes; there may be errors in the sample of sites; and nucleotides of different site positions are considered to be mutually dependent. In this algorithm, the site set is divided into subsets, each described by a certain consensus.