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
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Journal ArticleDOI
DNA microarray technology and its applications in dermatology
TL;DR: An overview on the basic DNA microarray technology and biostatistical methods for gene expression analysis and its applications in dermatological research is provided, which may help understand the complex pathogenesis of a wide variety of dermatologic diseases and identify their genetic background.
Journal ArticleDOI
A robust neural networks approach for spatial and intensity-dependent normalization of cDNA microarray data
A. L. Tarca,J. E. K. Cooke +1 more
TL;DR: A comparison of the robust neural network method with other published methods demonstrates its potential in reducing both intensity- dependent bias and spatial-dependent bias, which translates to more reliable identification of truly regulated genes.
Journal ArticleDOI
Impact of human donor lung gene expression profiles on survival after lung transplantation: a case-control study.
Masaki Anraku,Mark J. Cameron,Thomas K. Waddell,Mingyao Liu,Tamara Arenovich,Masaaki Sato,Marcelo Cypel,Andrew F. Pierre,M. de Perrot,David J. Kelvin,Shaf Keshavjee +10 more
TL;DR: This type of biological donor lung assessment shows significant promise for development of a more accurate diagnostic strategy to assess donor lungs prior to implantation.
Journal ArticleDOI
Comparative transcriptome analysis of two olive cultivars in response to NaCl-stress.
Christos Bazakos,Maria Manioudaki,Ioannis Therios,D.G. Voyiatzis,Dimitris Kafetzopoulos,Tala Awada,Panagiotis Kalaitzis +6 more
TL;DR: A comparative transcriptomics approach was used as a tool to unravel gene regulatory networks underlying salinity response in olive trees by simulating as much as possible olive growing conditions in the field, and differentially expressed transcripts as well as regulatory interactions were identified.
Journal ArticleDOI
Host Transcript Accumulation during Lytic KSHV Infection Reveals Several Classes of Host Responses
Sanjay Chandriani,Don Ganem +1 more
TL;DR: The results affirm that the levels of over 75% of host transcripts are substantially reduced during lytic infection, but also show that another ∼20% of cellular mRNAs declines only slightly (less than 2-fold) during the course of infection.
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