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Protein-structure-guided discovery of functional mutations across 19 cancer types
2016
Nature Genetics
Local concentrations of mutations are well-known in human cancers. However, their 3dimensional (3D) spatial relationships have yet to be systematically explored. We developed a computational tool, HotSpot3D, to identify such spatial hotspots (clusters) and to interpret the potential function of variants within them. We applied HotSpot3D to >4,400 TCGA tumors across 19 cancer types, discovering >6,000 intra-and inter-molecular clusters, some of which showed
doi:10.1038/ng.3586
pmid:27294619
pmcid:PMC5315576
fatcat:nwtjc6bvl5ewrbes3zuc65jzgm