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Journal ArticleDOI

Microarray data normalization and transformation

John Quackenbush
- 01 Dec 2002 - 
- Vol. 32, Iss: 4, pp 496-501
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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.

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Citations
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The effect of heterogeneous Transcription Start Sites (TSS) on the translatome: implications for the mammalian cellular phenotype

TL;DR: The results point to considerable and distinct cell-specific 5′TL heterogeneity within both the transcriptome and translatome of the two cell lines analysed, which is in-line with the ribosome filter hypothesis which posits that the Ribosomal machine can selectively filter information from within the Transcriptome.
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A comparison of the Giardia lamblia trophozoite and cyst transcriptome using microarrays

TL;DR: A global view of the cyst and trophozoite transcriptome complements studies focused on the expression of selected genes during trophozite multiplication, encystation and excystation, and showed that transcripts of most genes are present at a lower level in cysts.
Journal ArticleDOI

Computational systems analysis of developmental toxicity: design, development and implementation of a Birth Defects Systems Manager (BDSM).

TL;DR: The initial design, development and implementation of a Birth Defects Systems Manager (BDSM) was motivated by the need for a computational-bioinformatics infrastructure to manage vast digital information from functional genomics and for a new knowledge environment specifically engineered for the analysis of developmental processes and toxicities.
Posted Content

A State-Space Modeling Framework for Engineering Blockchain-Enabled Economic Systems.

TL;DR: A formal framework is established, with tools from dynamical systems theory, to mathematically describe core concepts in blockchain-enabled networks and is applied to the Bitcoin network and recovers its key 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

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
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