Literature DB >> 12047881

Statistical intelligence: effective analysis of high-density microarray data.

Sorin Draghici1.   

Abstract

Microarrays enable researchers to interrogate thousands of genes simultaneously. A crucial step in data analysis is the selection of subsets of interesting genes from the initial set of genes. In many cases, especially when comparing genes expressed in a specific condition to a reference condition, the genes of interest are those which are differentially regulated. This review focuses on the methods currently available for the selection of such genes. Fold change, unusual ratio, univariate testing with correction for multiple experiments, ANOVA and noise sampling methods are reviewed and compared.

Mesh:

Year:  2002        PMID: 12047881     DOI: 10.1016/s1359-6446(02)02292-4

Source DB:  PubMed          Journal:  Drug Discov Today        ISSN: 1359-6446            Impact factor:   7.851


  25 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

Review 2.  Methods for transcriptional profiling in plants. Be fruitful and replicate.

Authors:  Blake C Meyers; David W Galbraith; Timothy Nelson; Vikas Agrawal
Journal:  Plant Physiol       Date:  2004-06-01       Impact factor: 8.340

Review 3.  The microarray data analysis process: from raw data to biological significance.

Authors:  N Eric Olson
Journal:  NeuroRx       Date:  2006-07

4.  Analysis of microarray experiments of gene expression profiling.

Authors:  Adi L Tarca; Roberto Romero; Sorin Draghici
Journal:  Am J Obstet Gynecol       Date:  2006-08       Impact factor: 8.661

5.  A novel signaling pathway impact analysis.

Authors:  Adi Laurentiu Tarca; Sorin Draghici; Purvesh Khatri; Sonia S Hassan; Pooja Mittal; Jung-Sun Kim; Chong Jai Kim; Juan Pedro Kusanovic; Roberto Romero
Journal:  Bioinformatics       Date:  2008-11-05       Impact factor: 6.937

6.  A systems biology approach for pathway level analysis.

Authors:  Sorin Draghici; Purvesh Khatri; Adi Laurentiu Tarca; Kashyap Amin; Arina Done; Calin Voichita; Constantin Georgescu; Roberto Romero
Journal:  Genome Res       Date:  2007-09-04       Impact factor: 9.043

7.  Fold-change threshold screening: a robust algorithm to unmask hidden gene expression patterns in noisy aggregated transcriptome data.

Authors:  Jonas Hausen; Jens C Otte; Uwe Strähle; Monika Hammers-Wirtz; Henner Hollert; Steffen H Keiter; Richard Ottermanns
Journal:  Environ Sci Pollut Res Int       Date:  2015-07-17       Impact factor: 4.223

8.  Microarray analysis of differentially expressed genes between Brassica napus strains with high- and low-oleic acid contents.

Authors:  Mei Guan; Xun Li; Chunyun Guan
Journal:  Plant Cell Rep       Date:  2011-12-28       Impact factor: 4.570

9.  Seasonal differences of gene expression profiles in song sparrow (Melospiza melodia) hypothalamus in relation to territorial aggression.

Authors:  Motoko Mukai; Kirstin Replogle; Jenny Drnevich; Gang Wang; Douglas Wacker; Mark Band; David F Clayton; John C Wingfield
Journal:  PLoS One       Date:  2009-12-04       Impact factor: 3.240

10.  Rapid sample processing for LC-MS-based quantitative proteomics using high intensity focused ultrasound.

Authors:  Daniel López-Ferrer; Tyler H Heibeck; Konstantinos Petritis; Kim K Hixson; Weijun Qian; Matthew E Monroe; Anoop Mayampurath; Ronald J Moore; Mikhail E Belov; David G Camp; Richard D Smith
Journal:  J Proteome Res       Date:  2008-08-08       Impact factor: 4.466

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