Estimating the effects of variants found in disease driver genes opens the door to
personalized therapeutic opportunities. Clinical associations and laboratory experiments …

Computational predictors of genetic variant effect have advanced rapidly in recent years.
These programs provide clinical and research laboratories with a rapid and scalable method …

The vast majority of coding variants are rare, and assessment of the contribution of rare
variants to complex traits is hampered by low statistical power and limited functional data …

SignalP is the currently most widely used program for prediction of signal peptides from
amino acid sequences. Proteins with signal peptides are targeted to the secretory pathway …

The assessment of variant effect predictor (VEP) performance is fraught with biases
introduced by benchmarking against clinical observations. In this study, building on our …

The emergence of SARS-CoV-2 variants stressed the demand for tools allowing to interpret
the effect of single amino acid variants (SAVs) on protein function. While Deep Mutational …

We present here a full update of the PMut predictor, active since 2005 and with a large
acceptance in the field of predicting Mendelian pathological mutations. PMut internal engine …

To deal with the huge number of novel protein‐coding variants identified by genome and
exome sequencing studies, many computational variant effect predictors (VEPs) have been …

Computational tools are widely used for interpreting variants detected in sequencing
projects. The choice of these tools is critical for reliable variant impact interpretation for …

Next‐generation sequencing methods have revolutionized the speed of generating variation
information. Sequence data have a plethora of applications and will increasingly be used for …