Journal ArticleDOI
Microarray data normalization and transformation
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TLDR
This review focuses on the much more mundane but indispensable tasks of 'normalizing' data from individual hybridizations to make meaningful comparisons of expression levels, and of 'transforming' them to select genes for further analysis and data mining.Abstract:
Underlying every microarray experiment is an experimental question that one would like to address. Finding a useful and satisfactory answer relies on careful experimental design and the use of a variety of data-mining tools to explore the relationships between genes or reveal patterns of expression. While other sections of this issue deal with these lofty issues, this review focuses on the much more mundane but indispensable tasks of 'normalizing' data from individual hybridizations to make meaningful comparisons of expression levels, and of 'transforming' them to select genes for further analysis and data mining.read more
Citations
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Crucial role of calbindin-D28k in the pathogenesis of Alzheimer's disease mouse model.
Sun Young Kook,Hyobin Jeong,Min Jueng Kang,Park R,Hong Joon Shin,Sun-Ho Han,Sung Min Son,Hyundong Song,Sung Hoon Baik,Minho Moon,Eugene C. Yi,Daehee Hwang,Inhee Mook-Jung +12 more
TL;DR: This is the first experimental evidence that removal of CB from amyloid precursor protein/presenilin transgenic mice aggravatesAD pathogenesis, suggesting that CB has a critical role in AD pathogenesis.
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Leaf hairs influence phytopathogenic fungus infection and confer an increased resistance when expressing a Trichoderma α-1,3-glucanase
TL;DR: Evidence is provided that indicates the influence of leaf trichomes on foliar fungal infections in Arabidopsis thaliana, probably by facilitating the adhesion of the fungal spores/hyphae to the leaf surface.
Journal ArticleDOI
Microarray analysis of gene expression: considerations in data mining and statistical treatment
Joseph S. Verducci,Vincent F. Melfi,Vincent F. Melfi,Shili Lin,Zailong Wang,Zailong Wang,Sashwati Roy,Chandan K. Sen +7 more
TL;DR: This review article discusses the choice of microarray platform, preprocessing raw data, differential expression and validation, clustering, annotation and functional characterization of genes, and pathway construction in light of emergent concepts and tools.
Journal ArticleDOI
Gene expression deconvolution in linear space.
Yi Zhong,Zhandong Liu +1 more
TL;DR: GeneProf is a user-friendly platform for the analysis of gene expression designed to cater to four groups of users, and can be used to reanalyze over eight billion short read sequences from 752 high-throughput sequencing runs in a growing database of curated RNA-seq and chromatinimmunoprecipitation experiments.
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Identification of genes preferentially expressed by microglia and upregulated during cuprizone-induced inflammation
TL;DR: The identification of new selective markers for microglia are reported, which should prove useful not only to identify and isolate these cells, but also to better understand their distinctive properties.
References
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Journal ArticleDOI
Cluster analysis and display of genome-wide expression patterns
TL;DR: A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression, finding in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function.
Book
Data Reduction and Error Analysis for the Physical Sciences
TL;DR: In this paper, Monte Carlo techniques are used to fit dependent and independent variables least squares fit to a polynomial least-squares fit to an arbitrary function fitting composite peaks direct application of the maximum likelihood.
Journal ArticleDOI
Data Reduction and Error Analysis for the Physical Sciences.
TL;DR: Numerical methods matrices graphs and tables histograms and graphs computer routines in Pascal and Monte Carlo techniques dependent and independent variables least-squares fit to a polynomial least-square fit to an arbitrary function fitting composite peaks direct application of the maximum likelihood.
Journal ArticleDOI
Robust Locally Weighted Regression and Smoothing Scatterplots
TL;DR: Robust locally weighted regression as discussed by the authors is a method for smoothing a scatterplot, in which the fitted value at z k is the value of a polynomial fit to the data using weighted least squares, where the weight for (x i, y i ) is large if x i is close to x k and small if it is not.
Book
Regression Analysis by Example
Samprit Chatterjee,B. Price +1 more
TL;DR: Simple linear regression Multiple linear regression Regression Diagnostics: Detection of Model Violations Qualitative Variables as Predictors Transformation of Variables Weighted Least Squares The Problem of Correlated Errors Analysis of Collinear Data Biased Estimation of Regression Coefficients Variable Selection Procedures Logistic Regression Appendix References as discussed by the authors