Normalization and analysis of DNA microarray data by self-consistency and local regression
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* Corresponding author: Thomas B Kepler kepler@santafe.edu
Genome Biology 2002, 3:research0037-research0037.12 doi:10.1186/gb-2002-3-7-research0037
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BioMed Central: 15 citations
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Use of normalization methods for analysis of microarrays containing a high degree of gene effects Terri T Ni, William J Lemon, Yu Shyr, Tao P Zhong BMC Bioinformatics 2008, 9:505 (28 November 2008) |
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A Marfan syndrome gene expression phenotype in cultured skin fibroblasts Zizhen Yao, Jochen C Jaeger, Walter L Ruzzo, Cecile Z Morale, Mary Emond, Uta Francke, Dianna M Milewicz, Stephen M Schwartz, Eileen R Mulvihill BMC Genomics 2007, 8:319 (12 September 2007) |
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Evaluating different methods of microarray data normalization André Fujita, João Sato, Leonardo Rodrigues, Carlos Ferreira, Mari Sogayar BMC Bioinformatics 2006, 7:469 (23 October 2006) |
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Correction of scaling mismatches in oligonucleotide microarray data Martino Barenco, Jaroslav Stark, Daniel Brewer, Daniela Tomescu, Robin Callard, Michael Hubank BMC Bioinformatics 2006, 7:251 (9 May 2006) |
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Pathway level analysis of gene expression using singular value decomposition John Tomfohr, Jun Lu, Thomas B Kepler BMC Bioinformatics 2005, 6:225 (12 September 2005) |
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Evaluation of normalization methods for cDNA microarray data by k-NN classification Wei Wu, Eric P Xing, Connie Myers, I Saira Mian, Mina J Bissell BMC Bioinformatics 2005, 6:191 (26 July 2005) Of forty-one strategies for removing dye biases in microarray data that were tested by k-NN leave-one-out-validation, three two-step processes, which removed intensity-dependent bias and local spatial effects, reduced classification errors most consistently and effectively across all data sets.
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Jun Lu, John K Tomfohr, Thomas B Kepler BMC Bioinformatics 2005, 6:165 (29 June 2005) |
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An adaptive method for cDNA microarray normalization Yingdong Zhao, Ming-Chung Li, Richard Simon BMC Bioinformatics 2005, 6:28 (11 February 2005) |
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Model selection and efficiency testing for normalization of cDNA microarray data Matthias Futschik, Toni Crompton Genome Biology 2004, 5:R60 (30 July 2004) This study presents two novel normalization schemes for cDNA microarrays. They are based on iterative local regression and optimization of model parameters by generalized cross-validation. |
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Improving the scaling normalization for high-density oligonucleotide GeneChip expression microarrays Chao Lu BMC Bioinformatics 2004, 5:103 (29 July 2004) |
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Two-stage normalization using background intensities in cDNA microarray data Dankyu Yoon, Sung-Gon Yi, Ju-Han Kim, Taesung Park BMC Bioinformatics 2004, 5:97 (21 July 2004) |
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Jason Comander, Sripriya Natarajan, Michael A Gimbrone, Guillermo García-Cardeña BMC Genomics 2004, 5:17 (27 February 2004) |
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Tomokazu Konishi BMC Bioinformatics 2004, 5:5 (13 January 2004) |
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Evaluation of normalization methods for microarray data Taesung Park, Sung-Gon Yi, Sung-Hyun Kang, SeungYeoun Lee, Yong-Sung Lee, Richard Simon BMC Bioinformatics 2003, 4:33 (2 September 2003) |