Proteomic maps of breast cancer subtypes

[1]  Carlo Follo,et al.  PTEN deficiency and mutant p53 confer glucose-addiction to thyroid cancer cells: impact of glucose depletion on cell proliferation, cell survival, autophagy and cell migration , 2014, Genes & cancer.

[2]  Jeffrey R. Whiteaker,et al.  Proteogenomic characterization of human colon and rectal cancer , 2014, Nature.

[3]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[4]  Jun Yao,et al.  Loss of FBP1 by Snail-mediated repression provides metabolic advantages in basal-like breast cancer. , 2013, Cancer cell.

[5]  M. Mann,et al.  The coming age of complete, accurate, and ubiquitous proteomes. , 2013, Molecular cell.

[6]  Steven J. M. Jones,et al.  Comprehensive molecular portraits of human breast tumours , 2013 .

[7]  Matej Oresic,et al.  Integrated Systems and Technologies Metabolic Associations of Reduced Proliferation and Oxidative Stress in Advanced Breast Cancer , 2012 .

[8]  Jürgen Cox,et al.  1D and 2D annotation enrichment: a statistical method integrating quantitative proteomics with complementary high-throughput data , 2012, BMC Bioinformatics.

[9]  Steven J. M. Jones,et al.  Comprehensive molecular portraits of human breast tumors , 2012, Nature.

[10]  F. Markowetz,et al.  The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups , 2012, Nature.

[11]  Edwin de Jonge,et al.  Top-down Data Analysis with Treemaps , 2011, IMAGAPP/IVAPP.

[12]  Martin Kircher,et al.  Deep proteome and transcriptome mapping of a human cancer cell line , 2011, Molecular systems biology.

[13]  L. Pusztai,et al.  Gene expression profiling in breast cancer: classification, prognostication, and prediction , 2011, The Lancet.

[14]  M. Mann,et al.  Mass Spectrometry-based Proteomics Using Q Exactive, a High-performance Benchtop Quadrupole Orbitrap Mass Spectrometer* , 2011, Molecular & Cellular Proteomics.

[15]  M. Selbach,et al.  Global quantification of mammalian gene expression control , 2011, Nature.

[16]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[17]  M. Mann,et al.  Andromeda: a peptide search engine integrated into the MaxQuant environment. , 2011, Journal of proteome research.

[18]  이연수.  Functional genomics reveal that the serine synthesis pathway is essential in breast cancer , 2011 .

[19]  Xavier Robin,et al.  pROC: an open-source package for R and S+ to analyze and compare ROC curves , 2011, BMC Bioinformatics.

[20]  Matthias Mann,et al.  Proteomic Changes Resulting from Gene Copy Number Variations in Cancer Cells , 2010, PLoS genetics.

[21]  M. Mann,et al.  Proteome, phosphoproteome, and N-glycoproteome are quantitatively preserved in formalin-fixed paraffin-embedded tissue and analyzable by high-resolution mass spectrometry. , 2010, Journal of proteome research.

[22]  M. Mann,et al.  Super-SILAC mix for quantitative proteomics of human tumor tissue , 2010, Nature Methods.

[23]  Matthias Mann,et al.  Combination of FASP and StageTip-based fractionation allows in-depth analysis of the hippocampal membrane proteome. , 2009, Journal of proteome research.

[24]  A. Nobel,et al.  Supervised risk predictor of breast cancer based on intrinsic subtypes. , 2009, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[25]  C. Eyers.  Universal sample preparation method for proteome analysis , 2009 .

[26]  M. Mann,et al.  MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification , 2008, Nature Biotechnology.

[27]  Gianluca Bontempi,et al.  Biological Processes Associated with Breast Cancer Clinical Outcome Depend on the Molecular Subtypes , 2008, Clinical Cancer Research.

[28]  A. Regev,et al.  An embryonic stem cell–like gene expression signature in poorly differentiated aggressive human tumors , 2008, Nature Genetics.

[29]  John W M Martens,et al.  Subtypes of breast cancer show preferential site of relapse. , 2008, Cancer research.

[30]  L. Saal,et al.  Recurrent gross mutations of the PTEN tumor suppressor gene in breast cancers with deficient DSB repair , 2008, Nature Genetics.

[31]  V. Seewaldt,et al.  Interferon regulatory factor-1 regulates reconstituted extracellular matrix (rECM)-mediated apoptosis in human mammary epithelial cells , 2007, Oncogene.

[32]  R. Schwabe,et al.  TLR4 enhances TGF-beta signaling and hepatic fibrosis. , 2007, Nature medicine.

[33]  W. Gerald,et al.  An estrogen receptor-negative breast cancer subset characterized by a hormonally regulated transcriptional program and response to androgen , 2006, Oncogene.

[34]  J. Foekens,et al.  Laser microdissection and microarray analysis of breast tumors reveal ER-α related genes and pathways , 2006, Oncogene.

[35]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[36]  David Cameron,et al.  Identification of molecular apocrine breast tumours by microarray analysis , 2005, Oncogene.

[37]  R. Tibshirani,et al.  Repeated observation of breast tumor subtypes in independent gene expression data sets , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[38]  J. Hiscott,et al.  Transcriptional Profiling of Interferon Regulatory Factor 3 Target Genes: Direct Involvement in the Regulation of Interferon-Stimulated Genes , 2002, Journal of Virology.

[39]  M. Mann,et al.  Stable Isotope Labeling by Amino Acids in Cell Culture, SILAC, as a Simple and Accurate Approach to Expression Proteomics* , 2002, Molecular & Cellular Proteomics.

[40]  Yudong D. He,et al.  Gene expression profiling predicts clinical outcome of breast cancer , 2002, Nature.

[41]  R. Tibshirani,et al.  Significance analysis of microarrays applied to the ionizing radiation response , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[42]  Christian A. Rees,et al.  Molecular portraits of human breast tumours , 2000, Nature.

[43]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[44]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .