Druggable Genome: Unlocking its Therapeutic Potential Through Analysis of Somatic Mutations

This white paper presents an innovative computational pipeline designed to identify somatic mutations and predict their functional impact without the need for matched normal tissue samples. Focused on bladder cancer, the study demonstrates how deep sequencing data can be effectively analyzed to distinguish cancer-specific mutations, map gene interaction networks, and classify mutation effects using advanced protein foundation models.