… and widely used machine learning approach, MutPred 10 , by … MutPred2 is a machine
learning-based method, and … of that study, we predict that the disruption of allosteric sites is an …

… exonic SREs into a simple splicing simulator was found to substantially improve the predictions
of a simple splicing … RBPs in splicing and to interpret variants that alter RBP binding. …

… a novel generalized deep learning framework, referred to as DeepGenGrep (Deep learning-based
model for genomic signals and regions prediction), for predicting multiple GSRs in the …

… 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, …

… exonic and intronic regions could also enhance (splicing … thus its mutations should impair
splicing globally. Compared to … well as deep-learning-based methods for predicting isoform …

… Incorporating known exonic SREs into a simple splicing … This two-step process ensures that
we predict splicing from a … RBPs in splicing and to interpret variants that alter RBP binding. …

… to predict splicing disruption caused by genetic variants and … the likelihood of a variant
disrupting splicing (27, 28). … silencing splicing in local regions, we defined an exonic splicing …

… regulatory sequences (intronic and exonic splicing silencers … can predict the consequence
only of variants affecting the 5’ … to identify splicing variants (MutPred Splice [41], Splice AI [42]…

… interpretation of variant categories beyond missense variants. Variants affecting splicing
contribute … SpliceAI significantly outperformed other splicing variant prediction methods in both …

… MutPred Splice concentrates only on the variants at coding regions, ie, … deep learning-based
tools to identify splice variants. It annotates the genetic variants with their predictive splicing …