Stephan Lauxmann

The paper reanalyzes exome sequencing data from rare disease cases to identify previously undetected copy number variants, resulting in diagnoses for 51 families and partial explanations for 34 individuals.

The paper develops a Bayesian framework to integrate functional evidence into clinical variant interpretation for epilepsy-related ion channel genes, identifying key parameters that influence pathogenicity classification.

The paper uses computational models to show that ion channel mutations affect neuronal firing differently across cell types, challenging the use of loss/gain of function classification for neuronal outcomes.

The paper predicts functional effects of missense variants in voltage-gated sodium and calcium channels using machine learning, achieving high accuracy in distinguishing gain and loss of function variants.