DriverML: a machine learning algorithm for identifying driver genes in cancer sequencing studies
出版年份 2019 全文链接
标题
DriverML: a machine learning algorithm for identifying driver genes in cancer sequencing studies
作者
关键词
-
出版物
NUCLEIC ACIDS RESEARCH
Volume -, Issue -, Pages -
出版商
Oxford University Press (OUP)
发表日期
2019-02-05
DOI
10.1093/nar/gkz096
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Discovering personalized driver mutation profiles of single samples in cancer by network control strategy
- (2018) Wei-Feng Guo et al. BIOINFORMATICS
- Molecular Determinants of Response to Anti–Programmed Cell Death (PD)-1 and Anti–Programmed Death-Ligand 1 (PD-L1) Blockade in Patients With Non–Small-Cell Lung Cancer Profiled With Targeted Next-Generation Sequencing
- (2018) Hira Rizvi et al. JOURNAL OF CLINICAL ONCOLOGY
- Cancer driver mutation prediction through Bayesian integration of multi-omic data
- (2018) Zixing Wang et al. PLoS One
- Discovery of Cancer Driver Long Noncoding RNAs across 1112 Tumour Genomes: New Candidates and Distinguishing Features
- (2017) Andrés Lanzós et al. Scientific Reports
- Transcriptional repression of SOCS3 mediated by IL-6/STAT3 signaling via DNMT1 promotes pancreatic cancer growth and metastasis
- (2016) Li Huang et al. JOURNAL OF EXPERIMENTAL & CLINICAL CANCER RESEARCH
- Unsupervised detection of cancer driver mutations with parsimony-guided learning
- (2016) Runjun D Kumar et al. NATURE GENETICS
- Functional interaction of histone deacetylase 5 (HDAC5) and lysine-specific demethylase 1 (LSD1) promotes breast cancer progression
- (2016) C Cao et al. ONCOGENE
- Evaluating the evaluation of cancer driver genes
- (2016) Collin J. Tokheim et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Systematic analysis of mutation distribution in three dimensional protein structures identifies cancer driver genes
- (2016) Akihiro Fujimoto et al. Scientific Reports
- MADGiC: a model-based approach for identifying driver genes in cancer
- (2015) Keegan D. Korthauer et al. BIOINFORMATICS
- DriverDBv2: a database for human cancer driver gene research
- (2015) I-Fang Chung et al. NUCLEIC ACIDS RESEARCH
- Deacetylation of HSPA5 by HDAC6 leads to GP78-mediated HSPA5 ubiquitination at K447 and suppresses metastasis of breast cancer
- (2015) Y-W Chang et al. ONCOGENE
- e-Driver: a novel method to identify protein regions driving cancer
- (2014) Eduard Porta-Pardo et al. BIOINFORMATICS
- Discovery of co-occurring driver pathways in cancer
- (2014) Junhua Zhang et al. BMC BIOINFORMATICS
- Discovery and saturation analysis of cancer genes across 21 tumour types
- (2014) Michael S. Lawrence et al. NATURE
- DawnRank: discovering personalized driver genes in cancer
- (2014) Jack P Hou et al. Genome Medicine
- DrGaP: A Powerful Tool for Identifying Driver Genes and Pathways in Cancer Sequencing Studies
- (2013) Xing Hua et al. AMERICAN JOURNAL OF HUMAN GENETICS
- OncodriveCLUST: exploiting the positional clustering of somatic mutations to identify cancer genes
- (2013) David Tamborero et al. BIOINFORMATICS
- Utilizing protein structure to identify non-random somatic mutations
- (2013) Gregory A Ryslik et al. BMC BIOINFORMATICS
- Cumulative Haploinsufficiency and Triplosensitivity Drive Aneuploidy Patterns and Shape the Cancer Genome
- (2013) Teresa Davoli et al. CELL
- Activation of mammalian target of rapamycin complex 1 (mTORC1) and Raf/Pyk2 by growth factor-mediated Eph receptor 2 (EphA2) is required for cholangiocarcinoma growth and metastasis
- (2013) Xiang-Dan Cui et al. HEPATOLOGY
- Systematic analysis of somatic mutations in phosphorylation signaling predicts novel cancer drivers
- (2013) J. Reimand et al. Molecular Systems Biology
- Mutational heterogeneity in cancer and the search for new cancer-associated genes
- (2013) Michael S. Lawrence et al. NATURE
- IntOGen-mutations identifies cancer drivers across tumor types
- (2013) Abel Gonzalez-Perez et al. NATURE METHODS
- Emerging patterns of somatic mutations in cancer
- (2013) Ian R. Watson et al. NATURE REVIEWS GENETICS
- DriverDB: an exome sequencing database for cancer driver gene identification
- (2013) Wei-Chung Cheng et al. NUCLEIC ACIDS RESEARCH
- Cancer Genome Landscapes
- (2013) B. Vogelstein et al. SCIENCE
- Comprehensive identification of mutational cancer driver genes across 12 tumor types
- (2013) David Tamborero et al. Scientific Reports
- DriverNet: uncovering the impact of somatic driver mutations on transcriptional networks in cancer
- (2013) Ali Bashashati et al. GENOME BIOLOGY
- Efficient methods for identifying mutated driver pathways in cancer
- (2012) Junfei Zhao et al. BIOINFORMATICS
- Predicting sample size required for classification performance
- (2012) Rosa L Figueroa et al. BMC Medical Informatics and Decision Making
- Functional impact bias reveals cancer drivers
- (2012) Abel Gonzalez-Perez et al. NUCLEIC ACIDS RESEARCH
- Exome sequencing reveals germline NPAT mutation as a candidate risk factor for Hodgkin lymphoma
- (2011) S. Saarinen et al. BLOOD
- 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
- Identifying cancer driver genes in tumor genome sequencing studies
- (2010) Ahrim Youn et al. BIOINFORMATICS
- Advances in understanding cancer genomes through second-generation sequencing
- (2010) Matthew Meyerson et al. NATURE REVIEWS GENETICS
- Induced G1 cell-cycle arrest controls replication-dependent histone mRNA 3′ end processing through p21, NPAT and CDK9
- (2010) J Pirngruber et al. ONCOGENE
- Automated Network Analysis Identifies Core Pathways in Glioblastoma
- (2010) Ethan Cerami et al. PLoS One
- Cancer-Specific High-Throughput Annotation of Somatic Mutations: Computational Prediction of Driver Missense Mutations
- (2009) H. Carter et al. CANCER RESEARCH
- The cancer genome
- (2009) Michael R. Stratton et al. NATURE
- Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt
- (2009) Steffen Durinck et al. Nature Protocols
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