Genome Biology

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Within the fold: assessing differential expression measures and reproducibility in microarray assays

Ivana V Yang, Emily Chen, Jeremy P Hasseman, Wei Liang, Bryan C Frank, Shuibang Wang, Vasily Sharov, Alexander I Saeed, Joseph White, Jerry Li, Norman H Lee, Timothy J Yeatman and John Quackenbush*

Genome Biology 2002, 3:research0062-research0062.12 doi:10.1186/gb-2002-3-11-research0062

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Research   Open Access

Elucidating the identity of resistance mechanisms to prednisolone exposure in acute lymphoblastic leukemia cells through transcriptomic analysis: A computational approach

Emmanouil G Sifakis, George I Lambrou, Andriana Prentza, Spiros Vlahopoulos, Dimitris Koutsouris, Fotini Tzortzatou-Stathopoulou, Aristotelis A Chatziioannou Journal of Clinical Bioinformatics 2011, 1:36 (20 December 2011)

Research article   Open Access

Meta-analysis of archived DNA microarrays identifies genes regulated by hypoxia and involved in a metastatic phenotype in cancer cells

Michael Pierre, Benoît DeHertogh, Anthoula Gaigneaux, Bertrand DeMeulder, Fabrice Berger, Eric Bareke, Carine Michiels, Eric Depiereux BMC Cancer 2010, 10:176 (30 April 2010)

Methodology article   Open Access

An efficient algorithm for the stochastic simulation of the hybridization of DNA to microarrays

Erdem Arslan, Ian J Laurenzi BMC Bioinformatics 2009, 10:411 (10 December 2009)

Methodology article   Open Access

Integrative modeling of transcriptional regulation in response to antirheumatic therapy

Michael Hecker, Robert Goertsches, Robby Engelmann, Hans-Juergen Thiesen, Reinhard Guthke BMC Bioinformatics 2009, 10:262 (24 August 2009)

Research article   Open Access

Continuous exposure to Plasmodium results in decreased susceptibility and transcriptomic divergence of the Anopheles gambiae immune system

Ruth Aguilar, Suchismita Das, Yuemei Dong, George Dimopoulos BMC Genomics 2007, 8:451 (5 December 2007)

Method   Open Access Highly Accessed

Normalization of two-channel microarrays accounting for experimental design and intensity-dependent relationships

Alan R Dabney, John D Storey Genome Biology 2007, 8:R44 (28 March 2007)

eCADS is a new method for multiple array normalization of two-channel microarrays that takes into account general experimental designs and intensity-dependent relationships and allows for a more efficient dye-swap design that requires only one array per sample pair.

Methodology article   Open Access Highly Accessed

Evaluating different methods of microarray data normalization

André Fujita, João Sato, Leonardo Rodrigues, Carlos Ferreira, Mari Sogayar BMC Bioinformatics 2006, 7:469 (23 October 2006)

Methodology article   Open Access

Novel design and controls for focused DNA microarrays: applications in quality assurance/control and normalization for the Health Canada ToxArray™

Carole L Yauk, Andrew Williams, Sherri Boucher, Lynn M Berndt, Gu Zhou, Jenny L Zheng, Andrea Rowan-Carroll, Hongyan Dong, Iain B Lambert, George R Douglas, Craig L Parfett BMC Genomics 2006, 7:266 (19 October 2006)

Research article   Open Access Highly Accessed

Gene expression profiling of Spodoptera frugiperda hemocytes and fat body using cDNA microarray reveals polydnavirus-associated variations in lepidopteran host genes transcript levels

M Barat-Houari, F Hilliou, F-X Jousset, L Sofer, E Deleury, J Rocher, M Ravallec, L Galibert, P Delobel, R Feyereisen, P Fournier, A-N Volkoff BMC Genomics 2006, 7:160 (21 June 2006)

Parasitic wasps can suppress their hosts’ defence mechanisms through the action of endosymbiotic polydnaviruses, as shown by changes in the transcript levels of specific host genes in the presence of such a virus.

Research article   Open Access Highly Accessed

Persisters: a distinct physiological state of E. coli

Devang Shah, Zhigang Zhang, Arkady B Khodursky, Niilo Kaldalu, Kristi Kurg, Kim Lewis BMC Microbiology 2006, 6:53 (12 June 2006)

Methodology article   Open Access Highly Accessed

Empirical array quality weights in the analysis of microarray data

Matthew E Ritchie, Dileepa Diyagama, Jody Neilson, Ryan van Laar, Alexander Dobrovic, Andrew Holloway, Gordon K Smyth BMC Bioinformatics 2006, 7:261 (19 May 2006)

A novel method for assessing microarray data of varying quality, using empirical weights to identify differentially expressed genes, offers advantages over traditional filtering-based approaches in experiments with some replication.

Research article   Open Access Highly Accessed

Gene expression profiling of lymphoblastoid cell lines from monozygotic twins discordant in severity of autism reveals differential regulation of neurologically relevant genes

Valerie W Hu, Bryan C Frank, Shannon Heine, Norman H Lee, John Quackenbush BMC Genomics 2006, 7:118 (18 May 2006)

Methodology article   Open Access

A universal reference sample derived from clone vector for improved detection of differential gene expression

Rishi L Khan, Gregory E Gonye, Guang Gao, James S Schwaber BMC Genomics 2006, 7:109 (5 May 2006)

Software   Open Access

CARMA: A platform for analyzing microarray datasets that incorporate replicate measures

Kevin A Greer, Matthew R McReynolds, Heddwen L Brooks, James B Hoying BMC Bioinformatics 2006, 7:149 (17 March 2006)

Research   Open Access Highly Accessed

Comparative evaluation of linear and exponential amplification techniques for expression profiling at the single-cell level

Tatiana Subkhankulova, Frederick J Livesey Genome Biology 2006, 7:R18 (7 March 2006)

Comparison of the performance of three methods for amplifying single-cell amounts of RNA for use in expression profiling shows that PCT amplification is more reliable than linear amplification.

Proceedings   Open Access

Microarray scanner calibration curves: characteristics and implications

Leming Shi, Weida Tong, Zhenqiang Su, Tao Han, Jing Han, Raj K Puri, Hong Fang, Felix W Frueh, Federico M Goodsaid, Lei Guo, William S Branham, James J Chen, Z Alex Xu, Stephen C Harris, Huixiao Hong, Qian Xie, Roger G Perkins, James C Fuscoe BMC Bioinformatics 2005, 6(Suppl 2):S11 (15 July 2005)

Research article   Open Access Highly Accessed

A generic approach for the design of whole-genome oligoarrays, validated for genomotyping, deletion mapping and gene expression analysis on Staphylococcus aureus

Yvan Charbonnier, Brian Gettler, Patrice François, Manuela Bento, Adriana Renzoni, Pierre Vaudaux, Werner Schlegel, Jacques Schrenzel BMC Genomics 2005, 6:95 (17 June 2005)

Methodology article   Open Access

Noise filtering and nonparametric analysis of microarray data underscores discriminating markers of oral, prostate, lung, ovarian and breast cancer

Virginie M Aris, Michael J Cody, Jeff Cheng, James J Dermody, Patricia Soteropoulos, Michael Recce, Peter P Tolias BMC Bioinformatics 2004, 5:185 (29 November 2004)

Research article   Open Access

Selection and validation of endogenous reference genes using a high throughput approach

Ping Jin, Yingdong Zhao, Yvonne Ngalame, Monica C Panelli, Dirk Nagorsen, Vladia Monsurró, Kina Smith, Nan Hu, Hua Su, Phil R Taylor, Francesco M Marincola, Ena Wang BMC Genomics 2004, 5:55 (13 August 2004)

Methodology article   Open Access

Improving the scaling normalization for high-density oligonucleotide GeneChip expression microarrays

Chao Lu BMC Bioinformatics 2004, 5:103 (29 July 2004)

Methodology article   Open Access

The limits of log-ratios

Vasily Sharov, Ka Kwong, Bryan Frank, Emily Chen, Jeremy Hasseman, Renee Gaspard, Yan Yu, Ivana Yang, John Quackenbush BMC Biotechnology 2004, 4:3 (8 March 2004)

Method   Open Access

Exploratory differential gene expression analysis in microarray experiments with no or limited replication

Alexander V Loguinov, I Saira Mian, Chris D Vulpe Genome Biology 2004, 5:R18 (1 March 2004)

An exploratory, data-oriented approach is described for identifying candidates for differential gene expression in cDNA microarray experiments in terms of α-outliers and outlier regions, using simultaneous tolerance intervals relative to the line of equivalence.

Methodology article   Open Access

Improving the statistical detection of regulated genes from microarray data using intensity-based variance estimation

Jason Comander, Sripriya Natarajan, Michael A Gimbrone, Guillermo García-Cardeña BMC Genomics 2004, 5:17 (27 February 2004)

Research article   Open Access

Whole-genome microarrays of fission yeast: characteristics, accuracy, reproducibility, and processing of array data

Rachel Lyne, Gavin Burns, Juan Mata, Chris J Penkett, Gabriella Rustici, Dongrong Chen, Cordelia Langford, David Vetrie, Jürg Bähler BMC Genomics 2003, 4:27 (10 July 2003)

Review   Free Highly Accessed

Statistical tests for differential expression in cDNA microarray experiments

Xiangqin Cui, Gary A Churchill Genome Biology 2003, 4:210 (17 March 2003)

The simplest statistical method for extracting biological information from microarray data is the t test. Analysis of variance (ANOVA) and the mixed ANOVA model are general and powerful approaches for more complex microarray experiments.