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Cancer-specific high-throughput annotation of somatic mutations: computational prediction of driver missense mutations.

, , , , , , , and . Cancer research, 69 (16): 6660--6667 (Aug 15, 2009)
DOI: 10.1158/0008-5472.can-09-1133

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Cancer-specific high-throughput annotation of somatic mutations: computational prediction of driver missense mutations., , , , , , , and . Cancer research, 69 (16): 6660--6667 (Aug 15, 2009)Erratum: Identifying mutation specific cancer pathways using a structurally resolved protein interaction network., , and . PSB, page 634. (2018)CRAVAT: cancer-related analysis of variants toolkit., , , , , , , , and . Bioinform., 29 (5): 647-648 (2013)Evaluation and accurate diagnoses of pediatric diseases using artificial intelligence, , , , , , , , , and 61 other author(s). Nature Medicine, 25 (3): 433--438 (2019)Predictive analyses of regulatory sequences with EUGENe., , , , , , , and . Nat. Comput. Sci., 3 (11): 946-956 (2023)A Probabilistic Model to Predict Clinical Phenotypic Traits from Genome Sequencing., , , , , , , , , and 2 other author(s). PLoS Comput. Biol., (2014)Extracting allelic read counts from 250, 000 human sequencing runs in Sequence Read Archive., , , and . PSB, page 196-207. (2019)Interaction Landscape of Inherited Polymorphisms with Somatic Events in Cancer, , , , , , , , , and 6 other author(s). Cancer Discovery, 7 (4): 410--423 (February 2017)Network-based stratification of tumor mutations, , , , and . Nature Methods, 10 (11): 1108--1115 (Sep 15, 2013)CHASM and SNVBox: toolkit for detecting biologically important single nucleotide mutations in cancer., , , , , and . Bioinform., 27 (15): 2147-2148 (2011)