Statistical Methods for Gene Expression Data |
Kim, Choongrak (Department of Statistics, Pusan National University) |
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Statistical challenges in functional genomics(with discussion)
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DOI ScienceOn |
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Clustering methods for the analysis of dna microarray data
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A Direct approach to false discovery rates
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A decision -theoretic generalization of on-line learning and an application to boosting
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Different types of diffuse large b-cell lymphoma identified by gene expression profiling
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Controlling the false discovery rate: A practical and powerful approach to multiple testing
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The control of the false discovery rate in multiple testing under dependency
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A generalized likelihood ratio test to identify differentially expressed genes from microarray data
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Expression profiling using cDNA microarrays
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Bootstrapping cluster analysis: Assessing the reliability of conclusions microarray experiments
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Classification of multiple cancer types by multicategory support vector machines using gene expression data
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High-density synthetic oilgonucleotide arrays
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Replicated microarray data
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Systematic variation in gene expression patterns in human cancer cell lines
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Assessing gene significance from cDNA microarray expression data via mixed models
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Ratio-based decisions and the quantitative analysis of cDNA microarray images
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Statistical issues in cDNA microarray data analysis,Functional Genomics
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Multiple hypothesis testing
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Identifying and quantifying sources of variation in microarray data using high-density cDNA membrance arrays
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Unfolding of microarray data
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Systematic variation in gene expression patterns in human cancer cell lines
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Singular value decomposition for genome-wide expression data prcessing and modeling
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Bagging predictors
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27 |
Knowledge-based analysis of microarray gene expression data by using support vector machines
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Identifying differentially expressed genes using false discovery rate controlling procedures
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New normalization methods for cDNA microarray data
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Comprehensive identification of cell cycle-regulated genes of the yeast saccaromyces cerevisiae by microarray hybridization
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DNA microarray experiments: Biological and technological aspects
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Interpreting patterns of gene expression with self-organizing mpas: Methods and applications to hematopoietic differentiation
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Importance of replication in microarray gene expression studies: statistical methods and evidence from repetitive cDNA hybridizations
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Distinctive gene expression patterns in human mammary epithelial cells and breast cancers
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36 |
Comparison of methods for image analysis on cDNA microarray data
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37 |
Ratio statistics of gene expression levels and applicatins to microarray data analysis
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38 |
Bagging to improve the accuracy of a clustering procedure
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39 |
Supervised harvesting of expression trees
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Adjustment of systematic microarray data biases
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Gene expression informatics - it's all in your mine
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Discriminatory analysis, nonparametric discrimination: consistency properties
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Molecular classification of cancer:class discovery and class prediction by gene expression monitoring
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Tissue classification with gene expression profiles
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Deriving quantitative conclusions from microarray expression data
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Quantitative monitoring of gene expression patterns with a complementary DNA microarray
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48 |
On differential variability of expression ratios : Improving statistical inference about gene expression changes from microarray data
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Analysis of variance for microarray data
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Unsupervised technique for robust target separation and analysis of DNA microarray spots through adaptive pixel clustering
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Operating characteristics and extensions of the false discovery rate problem
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Issues in cDNA microarray analysis: quality filtering, channel normalization, models of variations and assessment of gene effects
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Diagnosis of multiple cancer types by shrunken centroids of gene expression
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54 |
The transcriptional program of sporulation in budding yeast
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Non-linear normalization and background correction in one-channel cDNA microarray studies
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Empirical Bayes analysis of a microarray experiment
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Cluster analysis and display of genome-wide expression patterns
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Expression monitoring by hybridization to high-density oligonucleotide arrays
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Boosting for tumor classification with gene expression data
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Dynamic modeling of gene expression data
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Significance analysis of microarrays applied to the ionizing radiation response
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Fundamental patterns underlying gene expression profiles: Simplicity from complexity
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Plaid models for gene expression data
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Analyzing high-density oligonucleotide gene expression array data
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Normalization for cDNA microarray data in Microarrays: Optical Technologies and Informatics
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Improved background correction for spotted DNA microarrays
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A paradigm for class prediction using gene expression profiles
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Gene expression data analysis
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Unsupervised feature selection via two-way ordering in gene expression analysis
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Inference from clustering with application to gene-expression microarrays
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Bayesian models for gene expression with DNA microarray data
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Feature extraction and normalization algorithms for high-density oligonucleotide gene expression array data
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The use of multiple measurements in taxonomic problems
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DOI |
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Comparison of methods for the classification of tumors using gene expression data
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