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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Conserved transcription factor binding sites of cancer markers derived from primary lung adenocarcinoma microarrays
Yee Leng Yap,Maria Pik Wong,Xue Wu Zhang,David Hernandez,Robin Gras,David K. Smith,Antoine Danchin +6 more
TL;DR: This study searched beyond phenotypic gene expression profiles in cancer cells, in order to identify the more important regulatory transcription factors that caused these aberrations in gene expression.
Journal ArticleDOI
Transforming omics data into context: Bioinformatics on genomics and proteomics raw data
Paul Perco,Ronald Rapberger,Christian Siehs,Arno Lukas,Rainer Oberbauer,Gert Mayer,Bernd Mayer +6 more
TL;DR: This review provides an overview on computational procedures for analysis of genomic and proteomic data introducing a sequential analysis workflow: Explorative statistics for deriving a first, from the purely statistical viewpoint, relevant candidate gene/protein list, followed by co‐regulation and network analysis to biologically expand this core list toward functional networks and pathways.
Journal ArticleDOI
Molecular karyotyping and aneuploidy detection in Arabidopsis thaliana using quantitative fluorescent polymerase chain reaction
TL;DR: It is demonstrated that quantitative fluorescent-polymerase chain reaction (QF-PCR) can be used to simultaneously genotype and karyotype aneuploid and polyploid Arabidopsis thaliana and that the progeny of tetraploid individuals are screened and found that more than 25% were aneuPLoid.
Journal ArticleDOI
Using bioinformatics and genome analysis for new therapeutic interventions
David W. Mount,Ritu Pandey +1 more
TL;DR: Cancer bioinformatics deals with organizing and analyzing the data so that important trends and patterns can be identified and Therapeutic agents directed against these targets can be developed and evaluated.
Journal ArticleDOI
Hippocampal gene expression is modulated by hypergravity
A. Del Signore,S. Mandillo,A. Rizzo,E Di Mauro,Andrea Mele,Rodolfo Negri,Alberto Oliverio,Paola Paggi +7 more
TL;DR: Six genes directly or indirectly involved in synaptic transmission and plasticity were found to be significantly modulated by hypergravity and unaffected or only slightly affected by rotation, suggesting that this stimulus might induce plastic remodelling of the hippocampal circuits.
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