Microarray-based Gene Expression Analysis of Endocrine Systems: Principles of Experimental Design and Interpretation

[1]  B. Scheithauer,et al.  DNA microarrays , 2005, Endocrine.

[2]  T Haferlach,et al.  Consensus guidelines for microarray gene expression analyses in leukemia from three European leukemia networks , 2006, Leukemia.

[3]  L. Bubendorf,et al.  Extraction of high‐integrity RNA suitable for microarray gene expression analysis from long‐term stored human thyroid tissues , 2006, Pathology.

[4]  Martin Dufva,et al.  Reverse transcription using random pentadecamer primers increases yield and quality of resulting cDNA. , 2006, BioTechniques.

[5]  K. Leslie,et al.  Gene regulation profiles by progesterone and dexamethasone in human endometrial cancer Ishikawa H cells. , 2006, Gynecologic oncology.

[6]  G. Zoppini,et al.  Clustering of cardiovascular risk factors associated with the insulin resistance syndrome: assessment by principal component analysis in young hyperandrogenic women. , 2006, Diabetes care.

[7]  David Murphy,et al.  A comprehensive description of the transcriptome of the hypothalamoneurohypophyseal system in euhydrated and dehydrated rats , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[8]  Emmanuel Barillot,et al.  ITTACA: a new database for integrated tumor transcriptome array and clinical data analysis , 2005, Nucleic Acids Res..

[9]  R. Jensen,et al.  Estrogen's and progesterone's impact on gene expression in the mouse lacrimal gland. , 2006, Investigative ophthalmology & visual science.

[10]  D. Allison,et al.  Microarray data analysis: from disarray to consolidation and consensus , 2006, Nature Reviews Genetics.

[11]  Ming-Chung Li,et al.  Histological staining methods preparatory to laser capture microdissection significantly affect the integrity of the cellular RNA , 2006, BMC Genomics.

[12]  Philippe Dessen,et al.  Comparison of the latest commercial short and long oligonucleotide microarray technologies , 2006, BMC Genomics.

[13]  Marcel J. T. Reinders,et al.  The effect of oligonucleotide microarray data pre-processing on the analysis of patient-cohort studies , 2006, BMC Bioinformatics.

[14]  David B. Allison,et al.  The PowerAtlas: a power and sample size atlas for microarray experimental design and research , 2006, BMC Bioinformatics.

[15]  Patrik D'haeseleer,et al.  How does gene expression clustering work? , 2005, Nature Biotechnology.

[16]  Michael G. Barnes,et al.  Experimental comparison and cross-validation of the Affymetrix and Illumina gene expression analysis platforms , 2005, Nucleic acids research.

[17]  Charles Auffray,et al.  'The 39 steps' in gene expression profiling: critical issues and proposed best practices for microarray experiments. , 2005, Drug discovery today.

[18]  A. Weiner,et al.  Software L 2 L : a simple tool for discovering the hidden significance in microarray expression data , 2005 .

[19]  Mrunal A. Deshmukh,et al.  CisMols Analyzer: identification of compositionally similar cis-element clusters in ortholog conserved regions of coordinately expressed genes , 2005, Nucleic Acids Research.

[20]  Eugene Berezikov,et al.  CONREAL web server: identification and visualization of conserved transcription factor binding sites , 2005, Nucleic Acids Res..

[21]  John Quackenbush,et al.  Multiple-laboratory comparison of microarray platforms , 2005, Nature Methods.

[22]  Howard Y. Chang,et al.  Robustness, scalability, and integration of a wound-response gene expression signature in predicting breast cancer survival. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[23]  Stefan Michiels,et al.  Prediction of cancer outcome with microarrays: a multiple random validation strategy , 2005, The Lancet.

[24]  Gavin Sherlock,et al.  The Stanford Microarray Database accommodates additional microarray platforms and data formats , 2004, Nucleic Acids Res..

[25]  Dennis B. Troup,et al.  NCBI GEO: mining millions of expression profiles—database and tools , 2004, Nucleic Acids Res..

[26]  Gerben J Schaaf,et al.  Evaluation of the similarity of gene expression data estimated with SAGE and Affymetrix GeneChips , 2005, BMC Genomics.

[27]  J. Cobb,et al.  Global gene expression in neuroendocrine tumors from patients with the MEN1 syndrome , 2005, Molecular Cancer.

[28]  G. Churchill,et al.  A comparison of cDNA, oligonucleotide, and Affymetrix GeneChip gene expression microarray platforms. , 2004, Journal of biomolecular techniques : JBT.

[29]  Jean YH Yang,et al.  Bioconductor: open software development for computational biology and bioinformatics , 2004, Genome Biology.

[30]  Homin K. Lee,et al.  Coexpression analysis of human genes across many microarray data sets. , 2004, Genome research.

[31]  T. Barrette,et al.  ONCOMINE: a cancer microarray database and integrated data-mining platform. , 2004, Neoplasia.

[32]  Guy Perrière,et al.  Cross-platform comparison and visualisation of gene expression data using co-inertia analysis , 2003, BMC Bioinformatics.

[33]  J. Ioannidis,et al.  Predictive ability of DNA microarrays for cancer outcomes and correlates: an empirical assessment , 2003, The Lancet.

[34]  David M. Rocke,et al.  Transformation and normalization of oligonucleotide microarray data , 2003, Bioinform..

[35]  Brad T. Sherman,et al.  DAVID: Database for Annotation, Visualization, and Integrated Discovery , 2003, Genome Biology.

[36]  Haidong Wang,et al.  Discovering molecular pathways from protein interaction and gene expression data , 2003, ISMB.

[37]  Roded Sharan,et al.  CREME: a framework for identifying cis-regulatory modules in human-mouse conserved segments , 2003, ISMB.

[38]  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.

[39]  M. Radmacher,et al.  Pitfalls in the use of DNA microarray data for diagnostic and prognostic classification. , 2003, Journal of the National Cancer Institute.

[40]  A. Brazma,et al.  Towards reconstruction of gene networks from expression data by supervised learning , 2003, Genome Biology.

[41]  Stephen M. Hewitt,et al.  Post-analysis follow-up and validation of microarray experiments , 2002, Nature Genetics.

[42]  G. Churchill.  Fundamentals of experimental design for cDNA microarrays , 2002, Nature Genetics.

[43]  John Quackenbush.  Microarray data normalization and transformation , 2002, Nature Genetics.

[44]  Ravi Kothapalli,et al.  Microarray results: how accurate are they? , 2002, BMC Bioinformatics.

[45]  S. Sealfon,et al.  Accuracy and calibration of commercial oligonucleotide and custom cDNA microarrays. , 2002, Nucleic acids research.

[46]  Geoffrey J McLachlan,et al.  Selection bias in gene extraction on the basis of microarray gene-expression data , 2002, Proceedings of the National Academy of Sciences of the United States of America.

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

[48]  Tommi S. Jaakkola,et al.  Combining Location and Expression Data for Principled Discovery of Genetic Regulatory Network Models , 2001, Pacific Symposium on Biocomputing.

[49]  J. Shah,et al.  Clinical significance of molecular expression profiles of Hürthle cell tumors of the thyroid gland analyzed via tissue microarrays. , 2002, The American journal of pathology.

[50]  Jason E. Stewart,et al.  Minimum information about a microarray experiment (MIAME)—toward standards for microarray data , 2001, Nature Genetics.

[51]  D. Leroith,et al.  Insulin and IGF-1 induce different patterns of gene expression in mouse fibroblast NIH-3T3 cells: identification by cDNA microarray analysis. , 2001, Endocrinology.

[52]  Carsten O. Peterson,et al.  Estrogen receptor status in breast cancer is associated with remarkably distinct gene expression patterns. , 2001, Cancer research.

[53]  N. Datson,et al.  Identification of corticosteroid‐responsive genes in rat hippocampus using serial analysis of gene expression , 2001, The European journal of neuroscience.

[54]  B. Aronow,et al.  Microarray analysis of trophoblast differentiation: gene expression reprogramming in key gene function categories. , 2001, Physiological genomics.

[55]  J. Moul,et al.  Quantitative expression profile of androgen‐regulated genes in prostate cancer cells and identification of prostate‐specific genes , 2001, International journal of cancer.

[56]  P. Wincker,et al.  Transcriptome of a mouse kidney cortical collecting duct cell line: Effects of aldosterone and vasopressin , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[57]  P. Meltzer,et al.  Thyroid hormone regulation of hepatic genes in vivo detected by complementary DNA microarray. , 2000, Molecular endocrinology.

[58]  E. Winzeler,et al.  Genomics, gene expression and DNA arrays , 2000, Nature.

[59]  I S Kohane,et al.  Mutual information relevance networks: functional genomic clustering using pairwise entropy measurements. , 1999, Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing.

[60]  V. de Waard,et al.  Serial analysis of gene expression to assess the endothelial cell response to an atherogenic stimulus. , 1999, Gene.

[61]  P. Crino,et al.  Preparation of cDNA from single cells and subcellular regions. , 1999, Methods in enzymology.