Yuya Kobayashi

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 evaluates how updates to the Sherloc variant classification framework reduced variants of uncertain significance (VUS) and improved accuracy over time.

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