BMC Bioinformatics

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Comparison and evaluation of methods for generating differentially expressed gene lists from microarray data

Ian B Jeffery*, Desmond G Higgins and Aedín C Culhane

BMC Bioinformatics 2006, 7:359 doi:10.1186/1471-2105-7-359

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Genome-wide analysis of plant nat-siRNAs reveals insights into their distribution, biogenesis and function

Xiaoming Zhang, Jing Xia, Yifan E Lii, Blanca E Barrera-Figueroa, Xuefeng Zhou, Shang Gao, Lu Lu, Dongdong Niu, Zheng Chen, Christy Leung, Timothy Wong, Huiming Zhang, Jianhua Guo, Yi Li, Renyi Liu, Wanqi Liang, Jian-Kang Zhu, Weixiong Zhang, Hailing Jin Genome Biology 2012, 13:R20 (22 March 2012)

In Arabidopsis and rice, natural antisense transcripts are processed into siRNAs by DCL1 and DCL3

Proceedings   Open Access

Fold change and p-value cutoffs significantly alter microarray interpretations

Mark R Dalman, Anthony Deeter, Gayathri Nimishakavi, Zhong-Hui Duan BMC Bioinformatics 2012, 13(Suppl 2):S11 (13 March 2012)

Proceedings   Open Access

A robust tool for discriminative analysis and feature selection in paired samples impacts the identification of the genes essential for reprogramming lung tissue to adenocarcinoma

Swee Toh, Philip Prathipati, Efthimios Motakis, Chee Keong Kwoh, Surya Yenamandra, Vladimir A Kuznetsov BMC Genomics 2011, 12(Suppl 3):S24 (30 November 2011)

Methodology article   Open Access

SegMine workflows for semantic microarray data analysis in Orange4WS

Vid Podpečan, Nada Lavrač, Igor Mozetič, Petra Novak, Igor Trajkovski, Laura Langohr, Kimmo Kulovesi, Hannu Toivonen, Marko Petek, Helena Motaln, Kristina Gruden BMC Bioinformatics 2011, 12:416 (26 October 2011)

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Evaluating methods for ranking differentially expressed genes applied to microArray quality control data

Koji Kadota, Kentaro Shimizu BMC Bioinformatics 2011, 12:227 (6 June 2011)

Technical Note   Open Access

RankProdIt: A web-interactive Rank Products analysis tool

Emma Laing, Colin P Smith BMC Research Notes 2010, 3:221 (6 August 2010)

This article is part of a collection on Microarray normalization...

Methodology article   Open Access Highly Accessed

Validation of differential gene expression algorithms: Application comparing fold-change estimation to hypothesis testing

Corey M Yanofsky, David R Bickel BMC Bioinformatics 2010, 11:63 (28 January 2010)

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Meta-analysis of glioblastoma multiforme versus anaplastic astrocytoma identifies robust gene markers

Jonathan M Dreyfuss, Mark D Johnson, Peter J Park Molecular Cancer 2009, 8:71 (4 September 2009)

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A gene signature for post-infectious chronic fatigue syndrome

John W Gow, Suzanne Hagan, Pawel Herzyk, Celia Cannon, Peter O Behan, Abhijit Chaudhuri BMC Medical Genomics 2009, 2:38 (25 June 2009)

Methodology article   Open Access Highly Accessed

Comparison of small n statistical tests of differential expression applied to microarrays

Carl Murie, Owen Woody, Anna Y Lee, Robert Nadon BMC Bioinformatics 2009, 10:45 (3 February 2009)

Research   Open Access

A voting approach to identify a small number of highly predictive genes using multiple classifiers

Md Rafiul Hassan, M Maruf Hossain, James Bailey, Geoff Macintyre, Joshua WK Ho, Kotagiri Ramamohanarao BMC Bioinformatics 2009, 10(Suppl 1):S19 (30 January 2009)

Research   Open Access

Development and application of versatile high density microarrays for genome-wide analysis of Streptomyces coelicolor: characterization of the HspR regulon

Giselda Bucca, Emma Laing, Vassilis Mersinias, Nicholas Allenby, Douglas Hurd, Jolyon Holdstock, Volker Brenner, Marcus Harrison, Colin P Smith Genome Biology 2009, 10:R5 (16 January 2009)

Development of high-density microarrays for global analysis of gene expression and transcription factor binding in Streptomyces coelicolor suggests a novel role for HspR in stress adaptation.

Methodology article   Open Access Highly Accessed

Not proper ROC curves as new tool for the analysis of differentially expressed genes in microarray experiments

Stefano Parodi, Vito Pistoia, Marco Muselli BMC Bioinformatics 2008, 9:410 (3 October 2008)

"Not proper ROC curves" (NPRC) is a new approach identifying differentially expressed genes that would not be discovered by conventional microarray statistical analysis.

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The rules of gene expression in plants: Organ identity and gene body methylation are key factors for regulation of gene expression in Arabidopsis thaliana

Felipe F Aceituno, Nick Moseyko, Seung Y Rhee, Rodrigo A Gutiérrez BMC Genomics 2008, 9:438 (23 September 2008)

Methodology article   Open Access

A Population Proportion approach for ranking differentially expressed genes

Mugdha Gadgil BMC Bioinformatics 2008, 9:380 (18 September 2008)

Methodology article   Open Access

Combining Shapley value and statistics to the analysis of gene expression data in children exposed to air pollution

Stefano Moretti, Danitsja van Leeuwen, Hans Gmuender, Stefano Bonassi, Joost van Delft, Jos Kleinjans, Fioravante Patrone, Domenico Merlo BMC Bioinformatics 2008, 9:361 (2 September 2008)

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A weighted average difference method for detecting differentially expressed genes from microarray data

Koji Kadota, Yuji Nakai, Kentaro Shimizu Algorithms for Molecular Biology 2008, 3:8 (26 June 2008)

Research article   Open Access

A unified framework for finding differentially expressed genes from microarray experiments

Jahangheer S Shaik, Mohammed Yeasin BMC Bioinformatics 2007, 8:347 (18 September 2007)

Research article   Open Access

New pleiotropic effects of eliminating a rare tRNA from Streptomyces coelicolor, revealed by combined proteomic and transcriptomic analysis of liquid cultures

Andy Hesketh, Giselda Bucca, Emma Laing, Fiona Flett, Graham Hotchkiss, Colin P Smith, Keith F Chater BMC Genomics 2007, 8:261 (2 August 2007)

Research article   Open Access

Importance of data structure in comparing two dimension reduction methods for classification of microarray gene expression data

Caroline Truntzer, Catherine Mercier, Jacques Estève, Christian Gautier, Pascal Roy BMC Bioinformatics 2007, 8:90 (13 March 2007)