- Referenced in 99 articles
- Missing value estimation for DNA microarrays. Motivation: Gene expression microarray experiments can generate data sets ... estimation of missing values in gene microarray data. We implemented and evaluated three methods ... tools for accurate estimation of missing microarray data under a variety of conditions. Availability...
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- package sma: Statistical Microarray Analysis. The package contains some simple functions for exploratory microarray analysis...
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- tumor classification with gene expression data. Motivation: Microarray experiments are expected to contribute significantly ... several established class prediction tools for microarray data. Availability: Software for the modified boosting algorithms ... benchmark studies and for the simulation of microarray data are available as an R package...
- Referenced in 36 articles
- present ARACNE, a novel algorithm, using microarray expression profiles, specifically designed to scale ... both a realistic synthetic dataset and a microarray dataset from human B cells. On synthetic ... approach should enhance our ability to use microarray data to elucidate functional mechanisms that underlie...
- Referenced in 55 articles
- limma: Linear Models for Microarray Data. A survey is given of differential expression analyses using...
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- digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many...
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- Variance stabilization and calibration for microarray data Bioconductor version: Release (2.10) The package implements ... method for normalising microarray intensities, both between colours within array, and between arrays. The method ... likelihood estimator for the stochastic model of microarray data described in the references (see vignette...
- Referenced in 37 articles
- differentially expressed groups of genes from a microarray experiment. The groups of genes are externally...
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- Detecting Differential Gene Expression in DNA Microarrays. SAM is a computer package for correlating gene ... detecting differential gene expression in DNA microarrays. Some recently developed methodology for estimating false discovery...
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- Parametric Empirical Bayes Methods for Microarrays. We have developed an empirical Bayes methodology for gene...
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- context of cancer diagnosis using microarray data. Results: The gene selection method suggested in this...
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- search engine technology for the analysis of microarray experiments. Background: Interpretation of simple microarray experiments ... algorithm provides an alternative method of evaluating microarray experimental results which combines prior knowledge about...
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- performance, it will be applied to several microarray data sets. An R package penalized, which...
- Referenced in 12 articles
- free, open-source system for microarray data management and analysis. Microarrays have emerged ... support of our ongoing work in microarray analysis of gene expression, we developed a suite ... manage, and analyze effectively data from DNA microarray experiments. The TM4 suite of tools consist ... four major applications, Microarray Data Manager (MADAM), TIGR_Spotfinder, Microarray Data Analysis System (MIDAS...
- Referenced in 22 articles
- identifying differentially expressed genes in DNA microarray experiments...
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- context of a genome-scale experiment (DNA microarray, proteomics, etc.). Said procedure has been implemented...
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- Modern experimental techniques, as for example DNA microarrays, as a result usually produce a long...
- Referenced in 17 articles
- large body of methodology developed for microarrays. Simulation studies show that voom performs as well...
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- significantly differential expression profiles in time-course microarray experiments. Motivation: Multi-series time-course microarray ... both a real and a simulated microarray dataset. Availability: The method has been implemented...
- Referenced in 16 articles
- instance, during the early days of microarray technology, the number of probes on a cDNA...