… , CADD-Splice, we show that inclusion of splicing DNN effect … Variants disrupting splicing
are established contributors to … to successfully predict splice variants residing within exonic …

… of genomic variants affecting this process (splicing variants in … recent Machine Learning-based
algorithms, for the prediction of … MutPred Splice Impact of coding region substitutions on …

… predicting splice site and exonic splicing variants [10,11,12]. Moreover, the inherent limitations
of deep … variant disrupting canonical splicing, and the effect indicates the significance of a …

… that contextualize predicted effects of variants on splicing to make it easier to interpret …
10% of all exonic variants, including missense and nonsense variants, may alter splicing.However, …

… of variants affecting 5’ and 3’ splice sites, the impact of variants … performed with Splice AI
[18], a deep learning-based tool … predictions (MutPred Splice and Splice AI) or false positive …

… (deep exonic missense variants) disrupted normal splicing of … machine learning-based
computational tools failed to predict … predicted as splice-affecting by SpliceAI and MutPred Splice (…

… and those using machine learning principles. For variants affecting splicing, we review the
evolution of computational approaches designed to predict splicing affectation and highlight …

… MutPred Splice and MiSplice are unique in using DNA-seq data to predict for somatic variants
that may disrupt normal splicing of … a machine learning model to predict exonic nucleotide …

… MutPred Splice uses machine learning to predict the potential consequences of exonic changes
on pre-mRNA splicing [… -type and variant sequence features for machine learning-based …

… 359 mutations were predicted to alter either a … predicting splicing mutations that do not
directly alter splice site sequences. Notably, our exclusion of mutations that generate cryptic splice …