Evaluating different methods of microarray data normalization
暂无分享,去创建一个
João Ricardo Sato | Carlos Eduardo Ferreira | André Fujita | Mari Cleide Sogayar | Leonardo de Oliveira Rodrigues | J. Sato | A. Fujita | M. Sogayar | C. Ferreira | Leonardo de Oliveira Rodrigues | André Fujita
[1] Mike Rossner,et al. Show me the data , 2007, The Journal of cell biology.
[2] Jian Huang,et al. A Two-Way Semilinear Model for Normalization and Analysis of cDNA Microarray Data , 2005 .
[3] Jianqing Fan,et al. Semilinear High-Dimensional Model for Normalization of Microarray Data , 2005 .
[4] Kiyoshi Asai,et al. Extracting relations between promoter sequences and their strengths from microarray data , 2005, Bioinform..
[5] Cédric Archambeau,et al. Probabilistic models in noisy environments : and their application to a visual prosthesis for the blind/ , 2005 .
[6] Jian Huang,et al. A robust two-way semi-linear model for normalization of cDNA microarray data , 2005, BMC Bioinformatics.
[7] Ju Wang,et al. Normalization of cDNA microarray data using wavelet regressions. , 2004, Combinatorial chemistry & high throughput screening.
[8] Peter Johnstone,et al. Normalization of microarray data using a spatial mixed model analysis which includes splines , 2004, Bioinform..
[9] Bernhard Schölkopf,et al. A tutorial on support vector regression , 2004, Stat. Comput..
[10] P. Tam,et al. Normalization and analysis of cDNA microarrays using within-array replications applied to neuroblastoma cell response to a cytokine. , 2004, Proceedings of the National Academy of Sciences of the United States of America.
[11] A I Saeed,et al. TM4: a free, open-source system for microarray data management and analysis. , 2003, BioTechniques.
[12] J. Squire,et al. Chromosomal localization of DNA amplifications in neuroblastoma tumors using cDNA microarray comparative genomic hybridization. , 2003, Neoplasia.
[13] John Quackenbush. Microarray data normalization and transformation , 2002, Nature Genetics.
[14] Guy Perrière,et al. Between-group analysis of microarray data , 2002, Bioinform..
[15] Jerry Li,et al. Within the fold: assessing differential expression measures and reproducibility in microarray assays , 2002, Genome Biology.
[16] S. Knudsen,et al. A new non-linear normalization method for reducing variability in DNA microarray experiments , 2002, Genome Biology.
[17] T. Speed,et al. Design issues for cDNA microarray experiments , 2002, Nature Reviews Genetics.
[18] Douglas M. Hawkins,et al. A variance-stabilizing transformation for gene-expression microarray data , 2002, ISMB.
[19] Yoganand Balagurunathan,et al. Simulation of cDNA microarrays via a parameterized random signal model. , 2002, Journal of biomedical optics.
[20] T. Kepler,et al. Normalization and analysis of DNA microarray data by self-consistency and local regression , 2002, Genome Biology.
[21] R. Shippy,et al. An assessment of Motorola CodeLink microarray performance for gene expression profiling applications. , 2002, Nucleic acids research.
[22] S. Dudoit,et al. Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. , 2002, Nucleic acids research.
[23] Ronaldo Dias. A review of non-parametric curve estimation methods with application to Econometrics , 2002 .
[24] Jason E. Stewart,et al. Minimum information about a microarray experiment (MIAME)—toward standards for microarray data , 2001, Nature Genetics.
[25] D. Slonim,et al. Evaluation of normalization procedures for oligonucleotide array data based on spiked cRNA controls , 2001, Genome Biology.
[26] Terence P. Speed,et al. Normalization for cDNA microarry data , 2001, SPIE BiOS.
[27] C. Li,et al. Feature extraction and normalization algorithms for high‐density oligonucleotide gene expression array data , 2001, Journal of cellular biochemistry. Supplement.
[28] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[29] R. Vanderbei. LOQO:an interior point code for quadratic programming , 1999 .
[30] I. Johnstone,et al. Minimax estimation via wavelet shrinkage , 1998 .
[31] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[32] Dimitri P. Bertsekas,et al. Nonlinear Programming , 1997 .
[33] Charles K. Chui,et al. An Introduction to Wavelets , 1992 .
[34] W. Härdle. Smoothing Techniques: With Implementation in S , 1991 .
[35] G. McCormick. Nonlinear Programming: Theory, Algorithms and Applications , 1983 .
[36] L. Schumaker. Spline Functions: Basic Theory , 1981 .
[37] P. M. Prenter. Splines and variational methods , 1975 .
[38] H. L. Le Roy,et al. Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability; Vol. IV , 1969 .
[39] Olvi L. Mangasarian,et al. Nonlinear Programming , 1969 .
[40] Shun-ichi Amari,et al. A Theory of Pattern Recognition , 1968 .
[41] E. Nadaraya. On Non-Parametric Estimates of Density Functions and Regression Curves , 1965 .
[42] V. Vapnik,et al. A note one class of perceptrons , 1964 .
[43] G. S. Watson,et al. Smooth regression analysis , 1964 .
[44] E. Nadaraya. On Estimating Regression , 1964 .
[45] V. Vapnik. Pattern recognition using generalized portrait method , 1963 .