An Integrated Statistical Approach to Compare Transcriptomics Data Across Experiments: A Case Study on the Identification of Candidate Target Genes of the Transcription Factor PPARα
暂无分享,去创建一个
Mohammad Ohid Ullah | Michael Müller | Guido J.E.J. Hooiveld | G. Hooiveld | M. O. Ullah | Michael Müller
[1] J. Davis. Bioinformatics and Computational Biology Solutions Using R and Bioconductor , 2007 .
[2] W. Wahli,et al. Peroxisome proliferator-activated receptors: nuclear control of metabolism. , 1999, Endocrine reviews.
[3] Philip N Benfey,et al. Reconstructing regulatory network transitions. , 2011, Trends in cell biology.
[4] G. Hooiveld,et al. Exploration of PPAR functions by microarray technology--a paradigm for nutrigenomics. , 2007, Biochimica et biophysica acta.
[5] P. Farnham,et al. Genomic Approaches That Aid in the Identification of Transcription Factor Target Genes , 2004, Experimental biology and medicine.
[6] Joshua M. Stuart,et al. A Gene-Coexpression Network for Global Discovery of Conserved Genetic Modules , 2003, Science.
[7] D. Allison,et al. Microarray data analysis: from disarray to consolidation and consensus , 2006, Nature Reviews Genetics.
[8] James M. Ntambi,et al. Polyunsaturated fatty acid regulation of gene expression , 2001, Journal of Molecular Neuroscience.
[9] Y. Benjamini,et al. Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .
[10] Jean YH Yang,et al. Bioconductor: open software development for computational biology and bioinformatics , 2004, Genome Biology.
[11] L. Sanderson,et al. Comprehensive Analysis of PPARα-Dependent Regulation of Hepatic Lipid Metabolism by Expression Profiling , 2007, PPAR research.
[12] Michael Müller,et al. Peroxisome Proliferator-Activated Receptor Alpha Target Genes , 2010, PPAR research.
[13] W. Wahli,et al. The peroxisome proliferator‐activated receptor α regulates amino acid metabolism , 2001, FASEB journal : official publication of the Federation of American Societies for Experimental Biology.
[14] L. Aravind,et al. Methods to reconstruct and compare transcriptional regulatory networks. , 2009, Methods in molecular biology.
[15] S. Kersten,et al. Nutrigenomics: goals and strategies , 2003, Nature Reviews Genetics.
[16] B. Gregory,et al. Whole-genome microarrays: applications and technical issues. , 2009, Methods in molecular biology.
[17] Vincent Laudet,et al. Overview of Nomenclature of Nuclear Receptors , 2006, Pharmacological Reviews.
[18] A. Bracken,et al. Transcriptomics: unravelling the biology of transcription factors and chromatin remodelers during development and differentiation. , 2009, Seminars in cell & developmental biology.
[19] Gordon K. Smyth,et al. limma: Linear Models for Microarray Data , 2005 .
[20] S. Kersten,et al. Peroxisome proliferator-activated receptor α target genes , 2004, Cellular and Molecular Life Sciences CMLS.
[21] I. Issemann,et al. Activation of a member of the steroid hormone receptor superfamily by peroxisome proliferators , 1990, Nature.
[22] John Quackenbush. Microarray analysis and tumor classification. , 2006, The New England journal of medicine.
[23] T. Willson,et al. The PPARs: from orphan receptors to drug discovery. , 2000, Journal of medicinal chemistry.
[24] Martin Vingron,et al. Improved detection of overrepresentation of Gene-Ontology annotations with parent-child analysis , 2007, Bioinform..
[25] Rafael A. Irizarry,et al. A Model-Based Background Adjustment for Oligonucleotide Expression Arrays , 2004 .
[26] V. Barnett,et al. Applied Linear Statistical Models , 1975 .
[27] I. Rusyn,et al. Genomic Profiling in Nuclear Receptor-Mediated Toxicity , 2007, Toxicologic pathology.
[28] T. Pineau,et al. Targeted disruption of the alpha isoform of the peroxisome proliferator-activated receptor gene in mice results in abolishment of the pleiotropic effects of peroxisome proliferators , 1995, Molecular and cellular biology.
[29] R. Heidstra,et al. Microarray-based identification of transcription factor target genes. , 2011, Methods in molecular biology.
[30] Thomas Lengauer,et al. ROCR: visualizing classifier performance in R , 2005, Bioinform..
[31] Gary A. Churchill,et al. Analysis of Variance for Gene Expression Microarray Data , 2000, J. Comput. Biol..
[32] Martin Vingron,et al. Ontologizer 2.0 - a multifunctional tool for GO term enrichment analysis and data exploration , 2008, Bioinform..
[33] Rafael A. Irizarry,et al. Bioinformatics and Computational Biology Solutions using R and Bioconductor , 2005 .
[34] Ross Ihaka,et al. Gentleman R: R: A language for data analysis and graphics , 1996 .
[35] Michael H. Kutner. Applied Linear Statistical Models , 1974 .
[36] G. Gibson,et al. Analysis of variance of microarray data. , 2006, Methods in enzymology.
[37] R. Myers,et al. Evolving gene/transcript definitions significantly alter the interpretation of GeneChip data , 2005, Nucleic acids research.
[38] D. Koller,et al. From signatures to models: understanding cancer using microarrays , 2005, Nature Genetics.
[39] Eugene Kolker,et al. A note on the false discovery rate and inconsistent comparisons between experiments , 2008, Bioinform..