Literature DB >> 11747612

A model for measurement error for gene expression arrays.

D M Rocke1, B Durbin.   

Abstract

We introduce a model for measurement error in gene expression arrays as a function of the expression level. This model, together with analysis methods, data transformations, and weighting, allows much more precise comparisons of gene expression, and provides guidance for analysis of background, determination of confidence intervals, and preprocessing data for multivariate analysis.

Mesh：

Year:  2001        PMID： 11747612     DOI： 10.1089/106652701753307485

Source DB:  PubMed          Journal:  J Comput Biol        ISSN： 1066-5277            Impact factor:   1.479


  124 in total

1.  Testing for differentially expressed genes with microarray data.

Authors:  Chen-An Tsai; Yi-Ju Chen; James J Chen
Journal:  Nucleic Acids Res       Date:  2003-05-01       Impact factor: 16.971

2.  Matrix Factorization for Transcriptional Regulatory Network Inference.

Authors:  Michael F Ochs; Elana J Fertig
Journal:  IEEE Symp Comput Intell Bioinforma Comput Biol Proc       Date:  2012-05

3.  A mixture model approach to detecting differentially expressed genes with microarray data.

Authors:  Wei Pan; Jizhen Lin; Chap T Le
Journal:  Funct Integr Genomics       Date:  2003-07-01       Impact factor: 3.410

4.  A model-based analysis of microarray experimental error and normalisation.

Authors:  Yongxiang Fang; Andrew Brass; David C Hoyle; Andrew Hayes; Abdulla Bashein; Stephen G Oliver; David Waddington; Magnus Rattray
Journal:  Nucleic Acids Res       Date:  2003-08-15       Impact factor: 16.971

5.  Increased power for the analysis of label-free LC-MS/MS proteomics data by combining spectral counts and peptide peak attributes.

Authors:  Lee Dicker; Xihong Lin; Alexander R Ivanov
Journal:  Mol Cell Proteomics       Date:  2010-09-07       Impact factor: 5.911

6.  Synchronized age-related gene expression changes across multiple tissues in human and the link to complex diseases.

Authors:  Jialiang Yang; Tao Huang; Francesca Petralia; Quan Long; Bin Zhang; Carmen Argmann; Yong Zhao; Charles V Mobbs; Eric E Schadt; Jun Zhu; Zhidong Tu
Journal:  Sci Rep       Date:  2015-10-19       Impact factor: 4.379

7.  A dynamic balance between gene activation and repression regulates the shade avoidance response in Arabidopsis.

Authors:  Giovanna Sessa; Monica Carabelli; Massimiliano Sassi; Andrea Ciolfi; Marco Possenti; Francesca Mittempergher; Jorg Becker; Giorgio Morelli; Ida Ruberti
Journal:  Genes Dev       Date:  2005-12-01       Impact factor: 11.361

8.  Transcriptional changes in powdery mildew infected wheat and Arabidopsis leaves undergoing syringolin-triggered hypersensitive cell death at infection sites.

Authors:  Kathrin Michel; Olaf Abderhalden; Rémy Bruggmann; Robert Dudler
Journal:  Plant Mol Biol       Date:  2006-08-29       Impact factor: 4.076

9.  High-resolution spatial normalization for microarrays containing embedded technical replicates.

Authors:  Daniel S Yuan; Rafael A Irizarry
Journal:  Bioinformatics       Date:  2006-10-23       Impact factor: 6.937

10.  Correcting for gene-specific dye bias in DNA microarrays using the method of maximum likelihood.

Authors:  Ryan Kelley; Hoda Feizi; Trey Ideker
Journal:  Bioinformatics       Date:  2007-07-10       Impact factor: 6.937
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