Joanne L. Dickinson

CharacTERT classifies hTERT missense variants using machine learning models that integrate sequence and structure-based features, achieving high accuracy and sensitivity in predicting pathogenicity.

This study identifies knowledge gaps and concerns about germline genetic testing for prostate cancer through qualitative and survey methods, highlighting the need for improved patient education and toolkit accessibility.

This study evaluates in silico variant prediction tools for cancer genes, finding gene-specific performance issues and recommending validation for individual genes.

The paper identifies a gene and protein expression signature associated with HOXB13 G84E carrier status in prostate cancer using proteogenomic analysis.

This review identifies and summarizes patient-reported measures used in genetic testing for cancer, highlighting the need for more measures in non-breast cancers.

This paper reviews functional genomic assays for telomere biology disorder genes to assess their utility in variant classification.