MADGiC: a model-based approach for identifying driver genes in cancer
Published 2015 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
MADGiC: a model-based approach for identifying driver genes in cancer
Authors
Keywords
-
Journal
BIOINFORMATICS
Volume 31, Issue 10, Pages 1526-1535
Publisher
Oxford University Press (OUP)
Online
2015-01-09
DOI
10.1093/bioinformatics/btu858
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Mutascope: sensitive detection of somatic mutations from deep amplicon sequencing
- (2013) Shawn E. Yost et al. BIOINFORMATICS
- OncodriveCLUST: exploiting the positional clustering of somatic mutations to identify cancer genes
- (2013) David Tamborero et al. BIOINFORMATICS
- Mutational heterogeneity in cancer and the search for new cancer-associated genes
- (2013) Michael S. Lawrence et al. NATURE
- Tumor Mutation Burden Forecasts Outcome in Ovarian Cancer with BRCA1 or BRCA2 Mutations
- (2013) Nicolai Juul Birkbak et al. PLoS One
- Cancer Genome Landscapes
- (2013) B. Vogelstein et al. SCIENCE
- Differential Relationship of DNA Replication Timing to Different Forms of Human Mutation and Variation
- (2012) Amnon Koren et al. AMERICAN JOURNAL OF HUMAN GENETICS
- MuSiC: Identifying mutational significance in cancer genomes
- (2012) N. D. Dees et al. GENOME RESEARCH
- The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity
- (2012) Jordi Barretina et al. NATURE
- Functional impact bias reveals cancer drivers
- (2012) Abel Gonzalez-Perez et al. NUCLEIC ACIDS RESEARCH
- DNA replication timing and selection shape the landscape of nucleotide variation in cancer genomes
- (2012) Yong H Woo et al. Nature Communications
- De novo discovery of mutated driver pathways in cancer
- (2011) F. Vandin et al. GENOME RESEARCH
- Mutual exclusivity analysis identifies oncogenic network modules
- (2011) G. Ciriello et al. GENOME RESEARCH
- dbNSFP: A lightweight database of human nonsynonymous SNPs and their functional predictions
- (2011) Xiaoming Liu et al. HUMAN MUTATION
- Initial genome sequencing and analysis of multiple myeloma
- (2011) Michael A. Chapman et al. NATURE
- Predicting the functional impact of protein mutations: application to cancer genomics
- (2011) Boris Reva et al. NUCLEIC ACIDS RESEARCH
- Identifying cancer driver genes in tumor genome sequencing studies
- (2010) Ahrim Youn et al. BIOINFORMATICS
- Inference of patient-specific pathway activities from multi-dimensional cancer genomics data using PARADIGM
- (2010) Charles J. Vaske et al. BIOINFORMATICS
- Impact of replication timing on non-CpG and CpG substitution rates in mammalian genomes
- (2010) C. L. Chen et al. GENOME RESEARCH
- A method and server for predicting damaging missense mutations
- (2010) Ivan A Adzhubei et al. NATURE METHODS
- COSMIC: mining complete cancer genomes in the Catalogue of Somatic Mutations in Cancer
- (2010) S. A. Forbes et al. NUCLEIC ACIDS RESEARCH
- Accumulation of driver and passenger mutations during tumor progression
- (2010) I. Bozic et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- A small-cell lung cancer genome with complex signatures of tobacco exposure
- (2009) Erin D. Pleasance et al. NATURE
- Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm
- (2009) Prateek Kumar et al. Nature Protocols
- Somatic mutations affect key pathways in lung adenocarcinoma
- (2008) Li Ding et al. NATURE
- Comparison of aspects of smoking among the four histological types of lung cancer
- (2008) S A Kenfield et al. TOBACCO CONTROL
- High-Resolution Copy-Number Variation Map Reflects Human Olfactory Receptor Diversity and Evolution
- (2008) Yehudit Hasin et al. PLoS Genetics
Add your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload NowAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started