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	51.	Research Zebrafish reward mutants reveal novel transcripts mediating the behavioral effects of amphetamine Katharine J Webb, William HJ Norton, Dietrich Trümbach, Annemarie H Meijer, Jovica Ninkovic, Stefanie Topp, Daniel Heck, Carsten Marr, Wolfgang Wurst, Fabian J Theis, Herman P Spaink, Laure Bally-Cuif Genome Biology 2009, 10:R81 (31 July 2009) Abstract \| Full text \| PDF \| PubMed \| Editor’s summary Transcriptome analysis of a zebrafish mutant that does not respond to amphetamine identifies a network of coordinated gene regulation that may underlie the susceptibility to addiction.
	52.	Method Gene ontology analysis for RNA-seq: accounting for selection bias Matthew D Young, Matthew J Wakefield, Gordon K Smyth, Alicia Oshlack Genome Biology 2010, 11:R14 (4 February 2010) Abstract \| Full text \| PDF \| PubMed \| Cited on BioMed Central \| Editor’s summary GOseq is a method for GO analysis of RNA-seq data that takes into account the length bias inherent in RNA-seq
	53.	Research The GENCODE pseudogene resource Baikang Pei, Cristina Sisu, Adam Frankish, Cédric Howald, Lukas Habegger, Xinmeng Mu, Rachel Harte, Suganthi Balasubramanian, Andrea Tanzer, Mark Diekhans, Alexandre Reymond, Tim J Hubbard, Jennifer Harrow, Mark B Gerstein Genome Biology 2012, 13:R51 (5 September 2012) Abstract \| Full text \| PDF \| PubMed \| Cited on BioMed Central \| Editor’s summary The GENCODE pseudogene resource includes evidence for dead genes undergoing resurrection
	54.	Review Statistical tests for differential expression in cDNA microarray experiments Xiangqin Cui, Gary A Churchill Genome Biology 2003, 4:210 (17 March 2003) Abstract \| Full text \| PDF \| PubMed \| Cited on BioMed Central \| Editor’s summary 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.
	55.	Research RNA sequencing reveals sexually dimorphic gene expression before gonadal differentiation in chicken embryos and allows comprehensive annotation of W-chromosome genes Katie L Ayers, Nadia M Davidson, Diana Demiyah, Kelly N Roeszler, Frank Grutzner, Andrew H Sinclair, Alicia Oshlack, Craig A Smith Genome Biology 2013, 14:R26 (25 March 2013) Abstract \| Provisional PDF \| PubMed \| Editor’s summary A transcriptomic analysis of the chicken female-specific W sex chromosome sheds light on avian sex differentiation
	56.	Research Multi-tissue coexpression networks reveal unexpected subnetworks associated with disease Radu Dobrin, Jun Zhu, Cliona Molony, Carmen Argman, Mark L Parrish, Sonia Carlson, Mark F Allan, Daniel Pomp, Eric E Schadt Genome Biology 2009, 10:R55 (22 May 2009) Abstract \| Full text \| PDF \| PubMed \| Cited on BioMed Central \| Editor’s summary Tissue-to-tissue coexpression networks between genes in hypothalamus, liver or adipose tissue enable identification of obesity-specific genes.
	57.	Research Exploring systemic RNA interference in insects: a genome-wide survey for RNAi genes in Tribolium Yoshinori Tomoyasu, Sherry C Miller, Shuichiro Tomita, Michael Schoppmeier, Daniela Grossmann, Gregor Bucher Genome Biology 2008, 9:R10 (17 January 2008) Abstract \| Full text \| PDF \| PubMed \| Cited on BioMed Central \| Editor’s summary Tribolium resembles C. elegans in showing a robust systemic RNAi response, but does not have C. elegans-type RNAi mechanisms; insect systemic RNAi probably uses a different mechanism.
	58.	Research Moving pictures of the human microbiome J Gregory Caporaso, Christian L Lauber, Elizabeth K Costello, Donna Berg-Lyons, Antonio Gonzalez, Jesse Stombaugh, Dan Knights, Pawel Gajer, Jacques Ravel, Noah Fierer, Jeffrey I Gordon, Rob Knight Genome Biology 2011, 12:R50 (30 May 2011) Abstract \| Full text \| PDF \| PubMed \| Cited on BioMed Central \| F1000 Biology \| Editor’s summary The dynamism of microbiome populations is seen in daily samples from a landmark multi-body site, multi-individual study
	59.	Research Loss of genes implicated in gastric function during platypus evolution Gonzalo R Ordoñez, LaDeana W Hillier, Wesley C Warren, Frank Grützner, Carlos López-Otín, Xose S Puente Genome Biology 2008, 9:R81 (15 May 2008) Abstract \| Full text \| PDF \| PubMed \| Cited on BioMed Central \| Editor’s summary Several genes implicated in food digestion have been deleted or inactivated in platypus. This loss perhaps explains the anatomical and physiological differences in the gastrointestinal tract between monotremes and other vertebrates and provides insights into platypus genome evolution.
	60.	Research Taxonomic distribution of large DNA viruses in the sea Adam Monier, Jean-Michel Claverie, Hiroyuki Ogata Genome Biology 2008, 9:R106 (3 July 2008) Abstract \| Full text \| PDF \| PubMed \| Cited on BioMed Central \| Editor’s summary Phylogenetic mapping of metagenomics data reveals the taxonomic distribution of large DNA viruses in the sea, including giant viruses of the Mimiviridae family.
	61.	Method Systematic bioinformatic analysis of expression levels of 17,330 human genes across 9,783 samples from 175 types of healthy and pathological tissues Sami Kilpinen, Reija Autio, Kalle Ojala, Kristiina Iljin, Elmar Bucher, Henri Sara, Tommi Pisto, Matti Saarela, Rolf I Skotheim, Mari Björkman, John-Patrick Mpindi, Saija Haapa-Paananen, Paula Vainio, Henrik Edgren, Maija Wolf, Jaakko Astola, Matthias Nees, Sampsa Hautaniemi, Olli Kallioniemi Genome Biology 2008, 9:R139 (19 September 2008) Abstract \| Full text \| PDF \| PubMed \| Cited on BioMed Central \| Editor’s summary A method for the comparison of mRNA expression levels of most human genes across gene expression array experiments, and a database of the results, are presented.
	62.	Research Coding potential of the products of alternative splicing in human Guido Leoni, Loredana Le Pera, Fabrizio Ferrè, Domenico Raimondo, Anna Tramontano Genome Biology 2011, 12:R9 (20 January 2011) Abstract \| Full text \| PDF \| PubMed \| Editor’s summary Comparison of proteomic datasets with transcription libraries allows exploration of to what extent alternatively spliced variants are translated into variant proteins
	63.	Research Aging effects on DNA methylation modules in human brain and blood tissue Steve Horvath, Yafeng Zhang, Peter Langfelder, René S Kahn, Marco PM Boks, Kristel van Eijk, Leonard H van den Berg, Roel A Ophoff Genome Biology 2012, 13:R97 (3 October 2012) Abstract \| Full text \| PDF \| PubMed \| Cited on BioMed Central \| Editor’s summary An age-related co-methylation module in human brain and blood tissue includes genes associated with Alzheimer's disease
	64.	Comment Sequestration: inadvertently killing biomedical research to score political points Jeffrey T Leek, Steven L Salzberg Genome Biology 2013, 14:109 (27 March 2013) Abstract \| Full text \| PDF \| PubMed \| 1 comment \| Editor’s summary Steven Salzberg and Jeff Leek are concerned about the Sequester's impact on biomedical research, and argue for a change in policy direction
	65.	Research Social regulation of gene expression in human leukocytes Steve W Cole, Louise C Hawkley, Jesusa M Arevalo, Caroline Y Sung, Robert M Rose, John T Cacioppo Genome Biology 2007, 8:R189 (13 September 2007) Abstract \| Full text \| PDF \| PubMed \| Cited on BioMed Central \| Editor’s summary Analysis of differentially expressed in circulating leukocytes from people who chronically experienced high versus low levels of subjective social isolation (loneliness) revealed over-expression of some anti-inflammatory genes and under-expression of some pro-inflammatory genes.
	66.	Research Changes in protein expression during honey bee larval development Queenie WT Chan, Leonard J Foster Genome Biology 2008, 9:R156 (29 October 2008) Abstract \| Full text \| PDF \| PubMed \| Cited on BioMed Central \| Editor’s summary Mass spectrometry-based quantitative proteomics was used to quantify nearly 800 proteins during the honey bee larval development.
	67.	Correspondence Conversion of amino-acid sequence in proteins to classical music: search for auditory patterns Rie Takahashi, Jeffrey H Miller Genome Biology 2007, 8:405 (3 May 2007) Abstract \| Full text \| PDF \| PubMed \| Editor’s summary How to make music from the genome.
	68.	Research A metagenomic study of diet-dependent interaction between gut microbiota and host in infants reveals differences in immune response Scott Schwartz, Iddo Friedberg, Ivan V Ivanov, Laurie A Davidson, Jennifer S Goldsby, David B Dahl, Damir Herman, Mei Wang, Sharon M Donovan, Robert S Chapkin Genome Biology 2012, 13:r32 (30 April 2012) Abstract \| Full text \| PDF \| PubMed \| Editor’s summary A novel host-microbiome analysis method reveals a transcriptional immune response in the breast-fed infant gut associated with diet-specific microbiota
	69.	Review RNA polymerase II stalling: loading at the start prepares genes for a sprint Jia Wu, Michael Snyder Genome Biology 2008, 9:220 (2 May 2008) Abstract \| Full text \| PDF \| PubMed \| Cited on BioMed Central \| Editor’s summary Promoter-proximal polymerase II stalling prepares genes for prompt expression when signals are received.
	70.	Method Targeted next-generation sequencing of a cancer transcriptome enhances detection of sequence variants and novel fusion transcripts Joshua Z Levin, Michael F Berger, Xian Adiconis, Peter Rogov, Alexandre Melnikov, Timothy Fennell, Chad Nusbaum, Levi A Garraway, Andreas Gnirke Genome Biology 2009, 10:R115 (16 October 2009) Abstract \| Full text \| PDF \| PubMed \| Cited on BioMed Central \| Editor’s summary Combining next-generation sequencing with capture of sequences from a relevant subset of a transcriptome produces an enhanced view of this subset
	71.	Research Assaying the regulatory potential of mammalian conserved non-coding sequences in human cells Catia Attanasio, Alexandre Reymond, Richard Humbert, Robert Lyle, Michael S Kuehn, Shane Neph, Peter J Sabo, Jeff Goldy, Molly Weaver, Andrew Haydock, Kristin Lee, Michael Dorschner, Emmanouil T Dermitzakis, Stylianos E Antonarakis, John A Stamatoyannopoulos Genome Biology 2008, 9:R168 (2 December 2008) Abstract \| Full text \| PDF \| PubMed \| Cited on BioMed Central \| Editor’s summary The fraction of experimentally active conserved non-coding sequences within any given cell type is low, so classical assays are unlikely to expose their potential.
	72.	Research High resolution discovery and confirmation of copy number variants in 90 Yoruba Nigerians Hajime Matsuzaki, Pei-Hua Wang, Jing Hu, Rich Rava, Glenn K Fu Genome Biology 2009, 10:R125 (9 November 2009) Abstract \| Full text \| PDF \| PubMed \| Cited on BioMed Central \| Editor’s summary Most microRNAs have a stronger inhibitory effect in estrogen receptor-negative than in estrogen receptor-positive breast cancers.
	73.	Method miRTRAP, a computational method for the systematic identification of miRNAs from high throughput sequencing data David Hendrix, Michael Levine, Weiyang Shi Genome Biology 2010, 11:R39 (6 April 2010) Abstract \| Full text \| PDF \| PubMed \| Cited on BioMed Central \| Editor’s summary A novel method for prediction of miRs from deep sequencing data. Its utility is demonstrated when applied to Ciona data.
	74.	Research Modeling gene expression using chromatin features in various cellular contexts Xianjun Dong, Melissa C Greven, Anshul Kundaje, Sarah Djebali, James B Brown, Chao Cheng, Thomas R Gingeras, Mark Gerstein, Roderic Guigó, Ewan Birney, Zhiping Weng Genome Biology 2012, 13:R53 (5 September 2012) Abstract \| Full text \| PDF \| PubMed \| Cited on BioMed Central \| Editor’s summary Models for linking gene expression with chromatin features vary according to cellular context and RNA measurement method
	75.	Research Systems biology-defined NF-κB regulons, interacting signal pathways and networks are implicated in the malignant phenotype of head and neck cancer cell lines differing in p53 status Bin Yan, Guang Chen, Kunal Saigal, Xinping Yang, Shane T Jensen, Carter Van Waes, Christian J Stoeckert, Zhong Chen Genome Biology 2008, 9:R53 (11 March 2008) Abstract \| Full text \| PDF \| PubMed \| Editor’s summary Detailed analysis of NFκB regulons in 1,265 genes differentially expressed in head and neck cancer cell lines differing in p53 status revealed a cross talk between NFkB and specific signaling pathways.