SGDriver: a novel structural genomics-based approach to prioritize cancer related and potentially druggable somatic mutations

摘要: Background A huge volume of somatic mutations have been generated through large cancer genome sequencing projects such as The Cancer Genome Atlas (TCGA) and the International Consortium (ICGC). However, understanding functional consequences in translating results into clinical use remains a major challenge genomic studies. Thanks to rapid development structural technologies, X-ray NMR, amounts protein structure data during past decade, which enables us map features (i.e., protein-ligand binding sites) investigate their potential impacts[1,2].