Systematic integration of protein-affecting mutations, gene fusions, and copy number alterations into a comprehensive somatic mutational profile
暂无分享,去创建一个
[1] D. Hanahan. Hallmarks of Cancer: New Dimensions. , 2022, Cancer discovery.
[2] N. Crosetto,et al. Somatic Copy Number Alterations in Human Cancers: An Analysis of Publicly Available Data From The Cancer Genome Atlas , 2021, Frontiers in Oncology.
[3] Howard Y. Chang,et al. Extrachromosomal DNA is associated with oncogene amplification and poor outcome across multiple cancers , 2020, Nature Genetics.
[4] F. Sanz,et al. The DisGeNET knowledge platform for disease genomics: 2019 update , 2019, Nucleic Acids Res..
[5] Icgc,et al. Pan-cancer analysis of whole genomes , 2017, bioRxiv.
[6] By Michael Marron-stearns. 2019 Update : What to , 2019 .
[7] C. Cole,et al. The COSMIC Cancer Gene Census: describing genetic dysfunction across all human cancers , 2018, Nature Reviews Cancer.
[8] D. Hanahan,et al. Pan-Cancer Landscape of Aberrant DNA Methylation across Human Tumors. , 2018, Cell reports.
[9] Li Ding,et al. Comprehensive Characterization of Cancer Driver Genes and Mutations (vol 173, 371.e1, 2018) , 2018 .
[10] P. A. Futreal,et al. KMT2D/MLL2 inactivation is associated with recurrence in adult-type granulosa cell tumors of the ovary , 2018, Nature Communications.
[11] Alessandro Pastore,et al. KMT2C mediates the estrogen dependence of breast cancer through regulation of ERα enhancer function , 2018, Oncogene.
[12] Adrian V. Lee,et al. An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics , 2018, Cell.
[13] Steven J. M. Jones,et al. Comprehensive Characterization of Cancer Driver Genes and Mutations , 2018, Cell.
[14] Steven J. M. Jones,et al. The Immune Landscape of Cancer , 2018, Immunity.
[15] Li Ding,et al. Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines. , 2018, Cell systems.
[16] T. Hughes,et al. The Human Transcription Factors , 2018, Cell.
[17] Ming Tang,et al. TumorFusions: an integrative resource for cancer-associated transcript fusions , 2017, Nucleic Acids Res..
[18] Russell Bonneville,et al. Landscape of Microsatellite Instability Across 39 Cancer Types. , 2017, JCO precision oncology.
[19] L. Matthews,et al. Appraising the relevance of DNA copy number loss and gain in prostate cancer using whole genome DNA sequence data , 2017, PLoS genetics.
[20] Molly Megraw,et al. IndeCut evaluates performance of network motif discovery algorithms , 2017, bioRxiv.
[21] Min Zhao,et al. ONGene: A literature-based database for human oncogenes. , 2017, Journal of genetics and genomics = Yi chuan xue bao.
[22] Patrick J. Paddison,et al. Causal Mechanistic Regulatory Network for Glioblastoma Deciphered Using Systems Genetics Network Analysis. , 2016, Cell systems.
[23] K. Kinzler,et al. Evaluating the evaluation of cancer driver genes , 2016, Proceedings of the National Academy of Sciences.
[24] Zhongming Zhao,et al. TSGene 2.0: an updated literature-based knowledgebase for tumor suppressor genes , 2015, Nucleic Acids Res..
[25] Xia Li,et al. Construction and analysis of dynamic transcription factor regulatory networks in the progression of glioma , 2015, Scientific Reports.
[26] Elhanan Borenstein,et al. Conservation of trans-acting circuitry during mammalian regulatory evolution , 2014, Nature.
[27] Steven J. M. Jones,et al. Integrated Genomic Characterization of Papillary Thyroid Carcinoma , 2014, Cell.
[28] David Tamborero,et al. OncodriveROLE classifies cancer driver genes in loss of function and activating mode of action , 2014, Bioinform..
[29] John N. Weinstein,et al. PRADA: pipeline for RNA sequencing data analysis , 2014, Bioinform..
[30] Peter J. Bickel,et al. Comparative analysis of regulatory information and circuits across distant species , 2014, Nature.
[31] Daniel A Charlebois,et al. Coherent feedforward transcriptional regulatory motifs enhance drug resistance. , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.
[32] S. Gabriel,et al. Discovery and saturation analysis of cancer genes across 21 tumor types , 2014, Nature.
[33] S. Elledge,et al. Cumulative Haploinsufficiency and Triplosensitivity Drive Aneuploidy Patterns and Shape the Cancer Genome , 2013, Cell.
[34] Michael P. Schroeder,et al. IntOGen-mutations identifies cancer drivers across tumor types , 2013, Nature Methods.
[35] David Tamborero,et al. OncodriveCLUST: exploiting the positional clustering of somatic mutations to identify cancer genes , 2013, Bioinform..
[36] Steven A. Roberts,et al. Mutational heterogeneity in cancer and the search for new cancer genes , 2014 .
[37] K. Kinzler,et al. Cancer Genome Landscapes , 2013, Science.
[38] Edgar Wingender,et al. TFClass: an expandable hierarchical classification of human transcription factors , 2012, Nucleic Acids Res..
[39] Steven A. Roberts,et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes , 2013 .
[40] Shane J. Neph,et al. Circuitry and Dynamics of Human Transcription Factor Regulatory Networks , 2012, Cell.
[41] David Z. Chen,et al. Architecture of the human regulatory network derived from ENCODE data , 2012, Nature.
[42] Benjamin E. Gross,et al. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. , 2012, Cancer discovery.
[43] Greg Gibson,et al. Rare and common variants: twenty arguments , 2012, Nature Reviews Genetics.
[44] G. Getz,et al. GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers , 2011, Genome Biology.
[45] D. Hanahan,et al. Hallmarks of Cancer: The Next Generation , 2011, Cell.
[46] V. Hinman,et al. A conserved gene regulatory network subcircuit drives different developmental fates in the vegetal pole of highly divergent echinoderm embryos. , 2010, Developmental biology.
[47] Derek Y. Chiang,et al. The landscape of somatic copy-number alteration across human cancers , 2010, Nature.
[48] J. Paul,et al. New Dimensions , 2011 .
[49] Steve Horvath,et al. A Systems Genetics Approach Implicates USF1, FADS3, and Other Causal Candidate Genes for Familial Combined Hyperlipidemia , 2009, PLoS genetics.
[50] Steve Horvath,et al. Using genetic markers to orient the edges in quantitative trait networks: The NEO software , 2008, BMC Systems Biology.
[51] U. Alon. Network motifs: theory and experimental approaches , 2007, Nature Reviews Genetics.
[52] Sebastian Wernicke,et al. FANMOD: a tool for fast network motif detection , 2006, Bioinform..
[53] G. Collins. The next generation. , 2006, Scientific American.
[54] S. Shen-Orr,et al. Superfamilies of Evolved and Designed Networks , 2004, Science.
[55] S. Mangan,et al. Structure and function of the feed-forward loop network motif , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[56] William B. Kristan,et al. Faculty Opinions recommendation of Network motifs: simple building blocks of complex networks. , 2002 .
[57] S. Shen-Orr,et al. Network motifs: simple building blocks of complex networks. , 2002, Science.
[58] L. Hood,et al. A Genomic Regulatory Network for Development , 2002, Science.
[59] J. Collins,et al. Construction of a genetic toggle switch in Escherichia coli , 2000, Nature.
[60] D. Hanahan,et al. The Hallmarks of Cancer , 2000, Cell.