Lists of computational tools and bioinformatics resources for analysis of personal mutanomes in cancer

Cancer genomics resources
 TCGA and GDCThe Cancer Genome Atlas and Genomic Data Commons Data Portalhttps://portal.gdc.cancer.govChin et al. (2011)
 ICGCThe International Cancer Genome Consortiumhttps://icgc.orgMilius et al. (2014)
 CBioPortalProviding visualization, analysis and download of large-scale cancer genomics data sets.http://www.cbioportal.orgGao et al. (2013)
 COSMICComprehensive resources for curating somatic mutations et al. (2015)
Bioinformatics resources for protein structures
 PDBThe PDB is the global archive for experimentally determined, atomic-level three-dimensional structures of proteins, DNA, and RNA. et al. (2017)
 Interactome3DManually curated protein-protein interactions with known three-dimensional structure information.http://interactome3d.irbbarcelona.orgMosca et al. (2013)
 dSysMapdSysMap is a useful tool to study the network perturbations by genetic variants et al. (2015)
 Interactome INSIDERAn integrative structural and genomic resource for functional exploration of human disease mutations at multiple-scale, proteome-wide human interactomehttp://interactomeinsider.yulab.orgMeyer et al. (2018)
Mutational clustering tools on protein structures
 AlloDriverDetect druggable mutations via dysregulation of protein allosteric functions.NAShen et al. (2017)
 Cancer3DA useful tool to explore potential cancer drivers or pharmacogenomic biomarkers using protein structure information. et al. (2015)
 CLUMPSAssess the significance of mutational clustering in a given 3D structure.NAKamburov et al. (2015)
 HotSpot3DDetect mutation–mutation and mutation–drug clusters using three-dimensional protein structures.NANiu et al. (2016)
 KNMPxDetect a kinome-wide pharmacogenomic biomarkers via rewiring phosphorylation-related signaling networks and drug sensitivity/resistanceNAZhao et al. (2017)
 ReKINectDetect network-attacking mutations in phosphorylation-based signaling networks. et al. (2015)
 SGDriverA structural genomics-based method that detects mutation clustering on protein–ligand binding site residues via a Bayes inference statistical framework.NAZhao et al. (2016)