Noriko Tanabe

A germline and somatic mutation sorting (GeMSort) algorithm for extracting presumed germline pathogenic variants in liquid genomic profiling: Insights from Database of Center for Cancer Genomics and Advanced Therapeutics (C-CAT)

The paper develops a GeMSort algorithm to accurately distinguish germline from somatic variants in liquid biopsy genomic profiling using real-world data from over 11,000 patients.

A comprehensive workflow for target adaptive sampling long-read sequencing applied to hereditary cancer patient genomes

This study develops a computational workflow for target adaptive sampling long-read sequencing and applies it to hereditary cancer genomes to identify genetic variants and epigenetic changes.

Network-based pathogenicity prediction for variants of uncertain significance

This paper introduces PathoGN, a network-based method for predicting variant pathogenicity, which outperforms existing methods and identifies pathogenicity for 3,994 variants of uncertain significance.