Cancer-specific high-throughput annotation of somatic mutations: computational prediction of driver missense mutations
about
Cancer genome landscapesNavigating the rapids: the development of regulated next-generation sequencing-based clinical trial assays and companion diagnosticsBioinformatics for cancer immunology and immunotherapyEmerging patterns of somatic mutations in cancerIntegrated genomic analyses of ovarian carcinomaComputational characterisation of cancer molecular profiles derived using next generation sequencingHow do oncoprotein mutations rewire protein-protein interaction networks?The genetic landscape of the childhood cancer medulloblastomaDeriving a mutation index of carcinogenicity using protein structure and protein interfacesBioinformatics for personal genome interpretationA graph theoretic approach to utilizing protein structure to identify non-random somatic mutations.A spatial simulation approach to account for protein structure when identifying non-random somatic mutationsPredicting survival in head and neck squamous cell carcinoma from TP53 mutation.Exome-Scale Discovery of Hotspot Mutation Regions in Human Cancer Using 3D Protein Structure.Predicting disease-associated substitution of a single amino acid by analyzing residue interactions.Structural and functional impact of cancer-related missense somatic mutations.Utilizing protein structure to identify non-random somatic mutations.MuPIT interactive: webserver for mapping variant positions to annotated, interactive 3D structures.Hotspot activating PRKD1 somatic mutations in polymorphous low-grade adenocarcinomas of the salivary glands.CRCDA--Comprehensive resources for cancer NGS data analysis.MUFFINN: cancer gene discovery via network analysis of somatic mutation data.Knowledge-based data analysis comes of age.Network Analysis Reveals A Signaling Regulatory Loop in the PIK3CA-mutated Breast Cancer Predicting Survival Outcome.Integrated analysis of recurrent properties of cancer genes to identify novel driversImproving the prediction of the functional impact of cancer mutations by baseline tolerance transformation.Making sense of cancer genomic data.CHASM and SNVBox: toolkit for detecting biologically important single nucleotide mutations in cancer.Principles and strategies for developing network models in cancer.Identification and analysis of driver missense mutations using rotation forest with feature selection.Identification of driver and passenger DNA methylation in cancer by epigenomic analysis.Phylomedicine: an evolutionary telescope to explore and diagnose the universe of disease mutations.Expanding the computational toolbox for mining cancer genomes.Population genetics meets cancer genomics.Accumulation of driver and passenger mutations during tumor progression.Predicting cancer-associated germline variations in proteins.Predicting the functional consequences of cancer-associated amino acid substitutions.Ranking non-synonymous single nucleotide polymorphisms based on disease conceptsWhole-exome sequencing defines the mutational landscape of pheochromocytoma and identifies KMT2D as a recurrently mutated genePrioritization of driver mutations in pancreatic cancer using cancer-specific high-throughput annotation of somatic mutations (CHASM).Distinguishing between driver and passenger mutations in individual cancer genomes by network enrichment analysis.
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Cancer-specific high-throughput annotation of somatic mutations: computational prediction of driver missense mutations
description
article científic
@ca
article scientifique
@fr
articolo scientifico
@it
artigo científico
@pt
bilimsel makale
@tr
scientific article published on 04 August 2009
@en
vedecký článok
@sk
vetenskaplig artikel
@sv
videnskabelig artikel
@da
vědecký článek
@cs
name
Cancer-specific high-throughpu ...... n of driver missense mutations
@en
Cancer-specific high-throughpu ...... of driver missense mutations.
@nl
type
label
Cancer-specific high-throughpu ...... n of driver missense mutations
@en
Cancer-specific high-throughpu ...... of driver missense mutations.
@nl
prefLabel
Cancer-specific high-throughpu ...... n of driver missense mutations
@en
Cancer-specific high-throughpu ...... of driver missense mutations.
@nl
P2093
P2860
P50
P1433
P1476
Cancer-specific high-throughpu ...... n of driver missense mutations
@en
P2093
Hannah Carter
Leyla Isik
Rachel Karchin
Sining Chen
Svitlana Tyekucheva
P2860
P304
P356
10.1158/0008-5472.CAN-09-1133
P407
P577
2009-08-04T00:00:00Z