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Results 1 - 10
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1,371
Quality control and robust estimation for cdna microarrays with replicates
- J Am Stat Assoc
"... We consider robust estimation of gene intensities from cDNA microarray data with replicates. Several statistical methods for estimating gene intensities from microarrays have been proposed, but there has been little work on robust estimation. This is particularly relevant for experiments with replic ..."
Abstract
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Cited by 11 (5 self)
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We consider robust estimation of gene intensities from cDNA microarray data with replicates. Several statistical methods for estimating gene intensities from microarrays have been proposed, but there has been little work on robust estimation. This is particularly relevant for experiments
OPTIMAL FACTORIAL DESIGNS FOR CDNA MICROARRAY EXPERIMENTS
, 803
"... We consider cDNA microarray experiments when the cell populations have a factorial structure, and investigate the problem of their optimal designing under a baseline parametrization where the objects of interest differ from those under the more common orthogonal parametrization. First, analytical re ..."
Abstract
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Cited by 2 (0 self)
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We consider cDNA microarray experiments when the cell populations have a factorial structure, and investigate the problem of their optimal designing under a baseline parametrization where the objects of interest differ from those under the more common orthogonal parametrization. First, analytical
Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation
, 2002
"... There are many sources of systematic variation in cDNA microarray experiments which affect the measured gene expression levels (e.g. differences in labeling efficiency between the two fluorescent dyes). The term normalization refers to the process of removing such variation. A constant adjustment is ..."
Abstract
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Cited by 718 (9 self)
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There are many sources of systematic variation in cDNA microarray experiments which affect the measured gene expression levels (e.g. differences in labeling efficiency between the two fluorescent dyes). The term normalization refers to the process of removing such variation. A constant adjustment
Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments
- STATISTICA SINICA
, 2002
"... DNA microarrays are a new and promising biotechnology whichallows the monitoring of expression levels in cells for thousands of genes simultaneously. The present paper describes statistical methods for the identification of differentially expressed genes in replicated cDNA microarray experiments. A ..."
Abstract
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Cited by 438 (12 self)
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DNA microarrays are a new and promising biotechnology whichallows the monitoring of expression levels in cells for thousands of genes simultaneously. The present paper describes statistical methods for the identification of differentially expressed genes in replicated cDNA microarray experiments
Normal uniform mixture differential gene expression detection for cdna microarrays
- ISSN
, 2005
"... comments and use of data One of the primary tasks in analysing gene expression data is finding genes that are differentially expressed in different samples. Some of the more popular methods for cDNA microarray data are based on examining the ratio of expression levels in the two channels, or on usin ..."
Abstract
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Cited by 19 (1 self)
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comments and use of data One of the primary tasks in analysing gene expression data is finding genes that are differentially expressed in different samples. Some of the more popular methods for cDNA microarray data are based on examining the ratio of expression levels in the two channels
Model selection and efficiency testing for normalization of cdna microarray data
- Genome Biol
, 2004
"... We present in this study two novel normalization schemes for cDNA microarrays. They are based on iterative local regression and optimization of model parameters by generalized cross-validation. Permutation tests assessing the efficiency of normalization demonstrated that the proposed schemes have an ..."
Abstract
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Cited by 11 (1 self)
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We present in this study two novel normalization schemes for cDNA microarrays. They are based on iterative local regression and optimization of model parameters by generalized cross-validation. Permutation tests assessing the efficiency of normalization demonstrated that the proposed schemes have
RECOGNITION OF CDNA MICROARRAY IMAGE USING FEEDFORWARD ARTIFICIAL NEURAL NETWORK
"... Abstract The complementary DNA (cDNA) ..."
Ratio-Based Decisions and the Quantitative Analysis of cDNA Microarray Images
, 1997
"... Gene expression can be quantitatively analyzed by hybridizing fluor-tagged mRNA to targets on a cDNA microarray. Comparison of gene expression levels arising from cohybridized samples is achieved by taking ratios of average expression levels for individual genes. A novel method of image segmentation ..."
Abstract
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Cited by 366 (28 self)
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Gene expression can be quantitatively analyzed by hybridizing fluor-tagged mRNA to targets on a cDNA microarray. Comparison of gene expression levels arising from cohybridized samples is achieved by taking ratios of average expression levels for individual genes. A novel method of image
Using Error-Correcting Design To Improve Cdna Microarray Performance
"... The performance of cDNA microarrays in quantitating relative RNA abundance is limited by the quality of the arrayed spots and the signal to background ratios of the fluorescence images. As the number of spots on microarrays increase to accomodate the entire genome, so will the probability that one o ..."
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The performance of cDNA microarrays in quantitating relative RNA abundance is limited by the quality of the arrayed spots and the signal to background ratios of the fluorescence images. As the number of spots on microarrays increase to accomodate the entire genome, so will the probability that one
Comparison of discrimination methods for the classification of tumors using gene expression data
- JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
, 2002
"... A reliable and precise classification of tumors is essential for successful diagnosis and treatment of cancer. cDNA microarrays and high-density oligonucleotide chips are novel biotechnologies increasingly used in cancer research. By allowing the monitoring of expression levels in cells for thousand ..."
Abstract
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Cited by 770 (6 self)
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A reliable and precise classification of tumors is essential for successful diagnosis and treatment of cancer. cDNA microarrays and high-density oligonucleotide chips are novel biotechnologies increasingly used in cancer research. By allowing the monitoring of expression levels in cells
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