Jason Reuter

The paper uses single-cell RNA-seq and machine learning to classify CASR variants as gain- or loss-of-function, achieving high accuracy and clinical validation.

The paper measures the functional impact of over two thousand SOD1 missense variants using saturation mutagenesis and cell-based assays, reclassifying 41% of previously uncertain variants as pathogenic.

The paper presents a method to reduce clinical uncertainty in KCNH2-related long QT syndrome by using calibrated functional data to classify variants of uncertain significance.

The paper develops a machine learning platform to improve variant classification, reducing VUS rates and improving concordance with ClinVar submissions.

The paper creates a functional map of all possible missense variants in CHK2 to assess their impact on cancer risk.