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		<title>BMC Genomics - Most viewed articles</title>
		<link>http://www.biomedcentral.com/bmcgenomics/mostviewed/</link>
		<description>Most viewed articles in last 30 days from BMC Genomics (ISSN 1471-2164) published by 
				
				BioMed Central
		</description>
        <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
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				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2164/9/247"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2164/9/77"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2164/9/312"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2164/9/310"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2164/9/302"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2164/9/340"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2164/9/303"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2164/9/320"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2164/5/96"/>			    
            
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		<item rdf:about="http://www.biomedcentral.com/1471-2164/9/247">
            
            <title>Comparative genomic analysis of the gut bacterium Bifidobacterium longum reveals loci susceptible to deletion during pure culture growth</title>
			<description>Background:
Bifidobacteria are frequently proposed to be associated with good intestinal health primarily because of their overriding dominance in the feces of breast fed infants. However, clinical feeding studies with exogenous bifidobacteria show they don't remain in the intestine, suggesting they may lose competitive fitness when grown outside the gut.
Results:
To further the understanding of genetic attenuation that may be occurring in bifidobacteria cultures, we obtained the complete genome sequence of an intestinal isolate, Bifidobacterium longum DJO10A that was minimally cultured in the laboratory, and compared it to that of a culture collection strain, B. longum NCC2705. This comparison revealed colinear genomes that exhibited high sequence identity, except for the presence of 17 unique DNA regions in strain DJO10A and six in strain NCC2705. While the majority of these unique regions encoded proteins of diverse function, eight from the DJO10A genome and one from NCC2705, encoded gene clusters predicted to be involved in diverse traits pertinent to the human intestinal environment, specifically oligosaccharide and polyol utilization, arsenic resistance and lantibiotic production. Seven of these unique regions were suggested by a base deviation index analysis to have been precisely deleted from strain NCC2705 and this is substantiated by a DNA remnant from within one of the regions still remaining in the genome of NCC2705 at the same locus. This targeted loss of genomic regions was experimentally validated when growth of the intestinal B. longum in the laboratory for 1,000 generations resulted in two large deletions, one in a lantibiotic encoding region, analogous to a predicted deletion event for NCC2705. A simulated fecal growth study showed a significant reduced competitive ability of this deletion strain against Clostridium difficile and E. coli. The deleted region was between two IS30 elements which were experimentally demonstrated to be hyperactive within the genome. The other deleted region bordered a novel class of mobile elements, termed mobile integrase cassettes (MIC) substantiating the likely role of these elements in genome deletion events.
Conclusion:
Deletion of genomic regions, often facilitated by mobile elements, allows bifidobacteria to adapt to fermentation environments in a very rapid manner (2 genome deletions per 1,000 generations) and the concomitant loss of possible competitive abilities in the gut.</description>
			<link>http://www.biomedcentral.com/1471-2164/9/247</link>		
			<dc:creator>Ju-Hoon Lee, VN Karamychev, SA Kozyavkin, D Mills, AR Pavlov, NV Pavlova, NN Polouchine, PM Richardson, VV Shakhova, AI Slesarev, B Weimer and DJ O'Sullivan</dc:creator>
			<dc:source>BMC Genomics 2008, 9:247</dc:source>
			<dc:subject>Number of accesses: 2816</dc:subject>
			<dc:date>2008-05-27</dc:date>
			<dc:identifier>doi:10.1186/1471-2164-9-247</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genomics</prism:publicationName>
					
			
							
					<prism:issn>1471-2164</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>247</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-05-27</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2164/9/77">
            
            <title>Mobile phone radiation might alter protein expression in human skin</title>
			<description>Background:
Earlier we have shown that the mobile phone radiation (radiofrequency modulated electromagnetic fields; RF-EMF) alters protein expression in human endothelial cell line. This does not mean that similar response will take place in human body exposed to this radiation. Therefore, in this pilot human volunteer study, using proteomics approach, we have examined whether a local exposure of human skin to RF-EMF will cause changes in protein expression in living people.
Results:
Small area of forearm's skin in 10 female volunteers was exposed to RF-EMF (specific absorption rate SAR = 1.3 W/kg) and punch biopsies were collected from exposed and non-exposed areas of skin. Proteins extracted from biopsies were separated using 2-DE and protein expression changes were analyzed using PDQuest software. Analysis has identified 8 proteins that were statistically significantly affected (Anova and Wilcoxon tests). Two of the proteins were present in all 10 volunteers. This suggests that protein expression in human skin might be affected by the exposure to RF-EMF. The number of affected proteins was similar to the number of affected proteins observed in our earlier in vitro studies.
Conclusion:
This is the first study showing that molecular level changes might take place in human volunteers in response to exposure to RF-EMF. Our study confirms that proteomics screening approach can identify protein targets of RF-EMF in human volunteers.</description>
			<link>http://www.biomedcentral.com/1471-2164/9/77</link>		
			<dc:creator>Anu Karinen, Sirpa Hein&#228;vaara, Reetta Nylund and Dariusz Leszczynski</dc:creator>
			<dc:source>BMC Genomics 2008, 9:77</dc:source>
			<dc:subject>Number of accesses: 1235</dc:subject>
			<dc:date>2008-02-11</dc:date>
			<dc:identifier>doi:10.1186/1471-2164-9-77</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genomics</prism:publicationName>
					
			
							
					<prism:issn>1471-2164</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>77</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-02-11</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2164/9/312">
            
            <title>High-throughput gene and SNP discovery in Eucalyptus grandis, an uncharacterized genome</title>
			<description>Background:
Benefits from high-throughput sequencing using 454 pyrosequencing technology may be most apparent for species with high societal or economic value but few genomic resources. Rapid means of gene sequence and SNP discovery using this novel sequencing technology provide a set of baseline tools for genome-level research. However, it is questionable how effective the sequencing of large numbers of short reads for species with essentially no prior gene sequence information will support contig assemblies and sequence annotation.
Results:
With the purpose of generating the first broad survey of gene sequences in Eucalyptus grandis, the most widely planted hardwood tree species, we used 454 technology to sequence and assemble 148 Mbp of expressed sequences (EST). EST sequences were generated from a normalized cDNA pool comprised of multiple tissues and genotypes, promoting discovery of homologues to almost half of Arabidopsis genes, and a comprehensive survey of allelic variation in the transcriptome. By aligning the sequencing reads from multiple genotypes we detected 23,742 SNPs, 83% of which were validated in a sample. Genome-wide nucleotide diversity was estimated for 2,392 contigs using a modified theta (&#952;) parameter, adapted for measuring genetic diversity from polymorphisms detected by randomly sequencing a multi-genotype cDNA pool. Diversity estimates in non-synonymous nucleotides were on average 4x smaller than in synonymous, suggesting purifying selection. Non-synonymous to synonymous substitutions (Ka/Ks) among 2,001 contigs averaged 0.30 and was skewed to the right, further supporting that most genes are under purifying selection. Comparison of these estimates among contigs identified major functional classes of genes under purifying and diversifying selection in agreement with previous researches.
Conclusion:
In providing an abundance of foundational transcript sequences where limited prior genomic information existed, this work created part of the foundation for the annotation of the E. grandis genome that is being sequenced by the US Department of Energy. In addition we demonstrated that SNPs sampled in large-scale with 454 pyrosequencing can be used to detect evolutionary signatures among genes, providing one of the first genome-wide assessments of nucleotide diversity and Ka/Ks for a non-model plant species.</description>
			<link>http://www.biomedcentral.com/1471-2164/9/312</link>		
			<dc:creator>Evandro Novaes, Derek R Drost, William G Farmerie, Georgios J Pappas, Dario Grattapaglia, Ronald R Sederoff and Matias Kirst</dc:creator>
			<dc:source>BMC Genomics 2008, 9:312</dc:source>
			<dc:subject>Number of accesses: 905</dc:subject>
			<dc:date>2008-06-30</dc:date>
			<dc:identifier>doi:10.1186/1471-2164-9-312</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genomics</prism:publicationName>
					
			
							
					<prism:issn>1471-2164</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>312</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-06-30</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2164/9/310">
            
            <title>Meta-Analysis Approach identifies Candidate Genes and associated Molecular Networks for Type-2 Diabetes Mellitus</title>
			<description>Background:
Multiple functional genomics data for complex human diseases have been published and made available by researchers worldwide. The main goal of these studies is the detailed analysis of a particular aspect of the disease. Complementary, meta-analysis approaches try to extract supersets of disease genes and interaction networks by integrating and combining these individual studies using statistical approaches.
Results:
Here we report on a meta-analysis approach that integrates data of heterogeneous origin in the domain of type-2 diabetes mellitus (T2DM). Different data sources such as DNA microarrays and, complementing, qualitative data covering several human and mouse tissues are integrated and analyzed with a Bootstrap scoring approach in order to extract disease relevance of the genes. The purpose of the meta-analysis is two-fold: on the one hand it identifies a group of genes with overall disease relevance indicating common, tissue-independent processes related to the disease; on the other hand it identifies genes showing specific alterations with respect to a single study. Using a random sampling approach we computed a core set of 213 T2DM genes across multiple tissues in human and mouse, including well-known genes such as Pdk4, Adipoq, Scd, Pik3r1, Socs2 that monitor important hallmarks of T2DM, for example the strong relationship between obesity and insulin resistance, as well as a large fraction (128) of yet barely characterized novel candidate genes. Furthermore, we explored functional information and identified cellular networks associated with this core set of genes such as pathway information, protein-protein interactions and gene regulatory networks. Additionally, we set up a web interface in order to allow users to screen T2DM relevance for any - yet non-associated - gene.
Conclusion:
In our paper we have identified a core set of 213 T2DM candidate genes by a meta-analysis of existing data sources. We have explored the relation of these genes to disease relevant information and - using enrichment analysis - we have identified biological networks on different layers of cellular information such as signaling and metabolic pathways, gene regulatory networks and protein-protein interactions. The web interface is accessible via http://t2dm-geneminer.molgen.mpg.de.</description>
			<link>http://www.biomedcentral.com/1471-2164/9/310</link>		
			<dc:creator>Axel Rasche, Hadi Al-Hasani and Ralf Herwig</dc:creator>
			<dc:source>BMC Genomics 2008, 9:310</dc:source>
			<dc:subject>Number of accesses: 864</dc:subject>
			<dc:date>2008-06-30</dc:date>
			<dc:identifier>doi:10.1186/1471-2164-9-310</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genomics</prism:publicationName>
					
			
							
					<prism:issn>1471-2164</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>310</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-06-30</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2164/9/302">
            
            <title>Performance comparison of two microarray platforms to assess differential gene expression in human monocyte and macrophage cells</title>
			<description>Background:
In this study we assessed the respective ability of Affymetrix and Illumina microarray methodologies to answer a relevant biological question, namely the change in gene expression between resting monocytes and macrophages derived from these monocytes. Five RNA samples for each type of cell were hybridized to the two platforms in parallel. In addition, a reference list of differentially expressed genes (DEG) was generated from a larger number of hybridizations (mRNA from 86 individuals) using the RNG/MRC two-color platform.
Results:
Our results show an important overlap of the Illumina and Affymetrix DEG lists. In addition, more than 70% of the genes in these lists were also present in the reference list. Overall the two platforms had very similar performance in terms of biological significance, evaluated by the presence in the DEG lists of an excess of genes belonging to Gene Ontology (GO) categories relevant for the biology of monocytes and macrophages. Our results support the conclusion of the MicroArray Quality Control (MAQC) project that the criteria used to constitute the DEG lists strongly influence the degree of concordance among platforms. However the importance of prioritizing genes by magnitude of effect (fold change) rather than statistical significance (p-value) to enhance cross-platform reproducibility recommended by the MAQC authors was not supported by our data.
Conclusion:
Functional analysis based on GO enrichment demonstrates that the 2 compared technologies delivered very similar results and identified most of the relevant GO categories enriched in the reference list.</description>
			<link>http://www.biomedcentral.com/1471-2164/9/302</link>		
			<dc:creator>Seraya Maouche, Odette Poirier, Tiphaine Godefroy, Robert Olaso, Ivo Gut, Jean-Phillipe Collet, Gilles Montalescot and Fran&#231;ois Cambien</dc:creator>
			<dc:source>BMC Genomics 2008, 9:302</dc:source>
			<dc:subject>Number of accesses: 846</dc:subject>
			<dc:date>2008-06-25</dc:date>
			<dc:identifier>doi:10.1186/1471-2164-9-302</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genomics</prism:publicationName>
					
			
							
					<prism:issn>1471-2164</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>302</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-06-25</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2164/9/340">
            
            <title>Comparative transcriptomics of human multipotent stem cells during adipogenesis and osteoblastogenesis</title>
			<description>Background:
A reciprocal relationship between bone and fat development in osteoporosis is clinically well established. Some of the key molecular regulators involved in this  tissue replacement process have been identified. The detailed mechanisms governing the differentiation of mesenchymal stem cells (MSC) - the key cells involved - are however only now beginning to emerge. In an attempt to address the regulation of the adipocyte/osteoblast balance at the level of gene transcription in a comprehensive and unbiased manner, we performed a large-scale gene expression profiling study using a unique cellular model, human multipotent adipose tissue-derived stem cells (hMADS). 
Results:
The analysis of 1606 genes that were found to be differentially expressed between adipogenesis and osteoblastogenesis revealed gene repression to be most prevalent prior to commitment in both lineages. Computational analyses suggested that this gene repression is mediated by miRNAs. The transcriptional activation of lineage-specific molecular processes in both cases occurred predominantly after commitment. Analyses of the gene expression data and promoter sequences produced a set of 65 genes that are candidates for genes involved in the process of adipocyte/osteoblast commitment. Four of these genes were studied in more detail: LXRalpha and phospholipid transfer protein (PLTP) for adipogenesis, the nuclear receptor COUP-TF1 and one uncharacterized gene, TMEM135 for osteoblastogenesis. PLTP was secreted during both early and late time points of hMADS adipocyte differentiation. LXRalpha, COUP-TF1, and the transmembrane protein TMEM135 were studied in primary cultures of differentiating bone marrow stromal cells from healthy donors and were found to be transcriptionally activated in the corresponding lineages.
Conclusions:
Our results reveal gene repression as a predominant early mechanism before final cell commitment. We were moreover able to identify 65 genes as candidates for genes controlling the adipocyte/osteoblast balance and to further evaluate four of these. Additional studies will explore the precise role of these candidate genes in regulating the adipogenesis/osteoblastogenesis switch.</description>
			<link>http://www.biomedcentral.com/1471-2164/9/340</link>		
			<dc:creator>Marcel Scheideler, Christian Elabd, Laure-Emmanuelle Zaragosi, Chiara Chiellini, Hubert Hackl, Fatima Sanchez-Cabo, Sunaina Yadav, Kalina Duszka, Gerald Friedl, Christine Papak, Andreas Prokesch, Reinhard Windhager, Gerard Ailhaud, Christian Dani, Ez-Zoubir Amri and Zlatko Trajanoski</dc:creator>
			<dc:source>BMC Genomics 2008, 9:340</dc:source>
			<dc:subject>Number of accesses: 795</dc:subject>
			<dc:date>2008-07-17</dc:date>
			<dc:identifier>doi:10.1186/1471-2164-9-340</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genomics</prism:publicationName>
					
			
							
					<prism:issn>1471-2164</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>340</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-07-17</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2164/9/303">
            
            <title>Proteomic profile of dormant Trichophyton Rubrum conidia</title>
			<description>Background:
Trichophyton rubrum is the most common dermatophyte causing fungal skin infections in humans. Asexual sporulation is an important means of propagation for T. rubrum, and conidia produced by this way are thought to be the primary cause of human infections. Despite their importance in pathogenesis, the conidia of T. rubrum remain understudied. We intend to intensively investigate the proteome of dormant T. rubrum conidia to characterize its molecular and cellular features and to enhance the development of novel therapeutic strategies.
Results:
The proteome of T. rubrum conidia was analyzed by combining shotgun proteomics with sample prefractionation and multiple enzyme digestion. In total, 1026 proteins were identified. All identified proteins were compared to those in the NCBI non-redundant protein database, the eukaryotic orthologous groups database, and the gene ontology database to obtain functional annotation information. Functional classification revealed that the identified proteins covered nearly all major biological processes. Some proteins were spore specific and related to the survival and dispersal of T. rubrum conidia, and many proteins were important to conidial germination and response to environmental conditions.
Conclusion:
Our results suggest that the proteome of T. rubrum conidia is considerably complex, and that the maintenance of conidial dormancy is an intricate and elaborate process. This data set provides the first global framework for the dormant T. rubrum conidia proteome and is a stepping stone on the way to further study of the molecular mechanisms of T. rubrum conidial germination and the maintenance of conidial dormancy.</description>
			<link>http://www.biomedcentral.com/1471-2164/9/303</link>		
			<dc:creator>Wenchuan Leng, Tao Liu, Rui Li, Jian Yang, Candong Wei, Wenliang Zhang and Qi Jin</dc:creator>
			<dc:source>BMC Genomics 2008, 9:303</dc:source>
			<dc:subject>Number of accesses: 761</dc:subject>
			<dc:date>2008-06-25</dc:date>
			<dc:identifier>doi:10.1186/1471-2164-9-303</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genomics</prism:publicationName>
					
			
							
					<prism:issn>1471-2164</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>303</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-06-25</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2164/9/320">
            
            <title>T2D-Db: An integrated platform to study the molecular basis of Type 2 diabetes</title>
			<description>Background:
Type 2 Diabetes Mellitus (T2DM) is a non insulin dependent, complex trait disease that develops due to genetic predisposition and environmental factors. The advanced stage in type 2 diabetes mellitus leads to several micro and macro vascular complications like nephropathy, neuropathy, retinopathy, heart related problems etc. Studies performed on the genetics, biochemistry and molecular biology of this disease to understand the pathophysiology of type 2 diabetes mellitus has led to the generation of a surfeit of data on candidate genes and related aspects. The research is highly progressive towards defining the exact etiology of this disease.
Results:
T2D-Db (Type 2 diabetes Database) is a comprehensive web resource, which provides integrated and curated information on almost all known molecular components involved in the pathogenesis of type 2 diabetes mellitus in the three widely studied mammals namely human, mouse and rat. Information on candidate genes, SNPs (Single Nucleotide Polymorphism) in candidate genes or candidate regions, genome wide association studies (GWA), tissue specific gene expression patterns, EST (Expressed Sequence Tag) data, expression information from microarray data, pathways, protein-protein interactions and disease associated risk factors or complications have been structured in this on line resource. 
Conclusion:
Information available in T2D-Db provides an integrated platform for the better molecular level understanding of type 2 diabetes mellitus and its pathogenesis. Importantly, the resource facilitates graphical presentation of the gene/genome wide map of SNP markers and protein-protein interaction networks, besides providing the heat map diagram of the selected gene(s) in an organism across microarray expression experiments from either single or multiple studies. These features aid to the data interpretation in an integrative way. T2D-Db is to our knowledge the first publicly available resource that can cater to the needs of researchers working on different aspects of type 2 diabetes mellitus. Availabilityhttp://t2ddb.ibab.ac.in  </description>
			<link>http://www.biomedcentral.com/1471-2164/9/320</link>		
			<dc:creator>Shipra Agrawal, Nevenka Dimitrova, Prasanthi Nathan, Udayakumar K., Sailakshmi S., Sriram S., Manjusha N and Urmi Sengupta</dc:creator>
			<dc:source>BMC Genomics 2008, 9:320</dc:source>
			<dc:subject>Number of accesses: 751</dc:subject>
			<dc:date>2008-07-07</dc:date>
			<dc:identifier>doi:10.1186/1471-2164-9-320</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genomics</prism:publicationName>
					
			
							
					<prism:issn>1471-2164</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>320</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-07-07</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2164/5/96">
            
            <title>FunnyBase: a systems level functional annotation of Fundulus ESTs for the analysis of gene expression</title>
			<description>Background:
While studies of non-model organisms are critical for many research areas, such as evolution, development, and environmental biology, they present particular challenges for both experimental and computational genomic level research. Resources such as mass-produced microarrays and the computational tools linking these data to functional annotation at the system and pathway level are rarely available for non-model species. This type of "systems-level" analysis is critical to the understanding of patterns of gene expression that underlie biological processes.
Results:
We describe a bioinformatics pipeline known as FunnyBase that has been used to store, annotate, and analyze 40,363 expressed sequence tags (ESTs) from the heart and liver of the fish, Fundulus heteroclitus. Primary annotations based on sequence similarity are linked to networks of systematic annotation in Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) and can be queried and computationally utilized in downstream analyses. Steps are taken to ensure that the annotation is self-consistent and that the structure of GO is used to identify higher level functions that may not be annotated directly. An integrated framework for cDNA library production, sequencing, quality control, expression data generation, and systems-level analysis is presented and utilized. In a case study, a set of genes, that had statistically significant regression between gene expression levels and environmental temperature along the Atlantic Coast, shows a statistically significant (P &lt; 0.001) enrichment in genes associated with amine metabolism.
Conclusion:
The methods described have application for functional genomics studies, particularly among non-model organisms. The web interface for FunnyBase can be accessed at http://genomics.rsmas.miami.edu/funnybase/super_craw4/. Data and source code are available by request at jpaschall@bioinfobase.umkc.edu.</description>
			<link>http://www.biomedcentral.com/1471-2164/5/96</link>		
			<dc:creator>Justin E Paschall, Marjorie F Oleksiak, Jeffrey D VanWye, Jennifer L Roach, J Andrew Whitehead, Gerald J Wyckoff, Kevin J Kolell and Douglas L Crawford</dc:creator>
			<dc:source>BMC Genomics 2004, 5:96</dc:source>
			<dc:subject>Number of accesses: 716</dc:subject>
			<dc:date>2004-12-20</dc:date>
			<dc:identifier>doi:10.1186/1471-2164-5-96</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genomics</prism:publicationName>
					
			
							
					<prism:issn>1471-2164</prism:issn>
					
			
							
					<prism:volume>5</prism:volume>
					
			
							
					<prism:startingPage>96</prism:startingPage>
					
			
							
					<prism:publicationDate>2004-12-20</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2164/9/301">
            
            <title>Differential gene expression of the honey bee Apis mellifera associated with Varroa destructor infection</title>
			<description>Background:
The parasitic mite, Varroa destructor, is the most serious pest of the western honey bee, Apis mellifera, and has caused the death of millions of colonies worldwide. This mite reproduces in brood cells and parasitizes immature and adult bees. We investigated whether Varroa infestation induces changes in Apis mellifera gene expression, and whether there are genotypic differences that affect gene expression relevant to the bee's tolerance, as first steps toward unravelling mechanisms of host response and differences in susceptibility to Varroa parasitism.
Results:
We explored the transcriptional response to mite parasitism in two genetic stocks of A. mellifera which differ in susceptibility to Varroa, comparing parasitized and non-parasitized full-sister pupae from both stocks. Bee expression profiles were analyzed using microarrays derived from honey bee ESTs whose annotation has recently been enhanced by results from the honey bee genome sequence. We measured differences in gene expression in two colonies of Varroa-susceptible and two colonies of Varroa-tolerant bees. We identified a set of 148 genes with significantly different patterns of expression: 32 varied with the presence of Varroa, 116 varied with bee genotype, and 2 with both. Varroa parasitism caused changes in the expression of genes related to embryonic development, cell metabolism and immunity. Bees tolerant to Varroa were mainly characterized by differences in the expression of genes regulating neuronal development, neuronal sensitivity and olfaction. Differences in olfaction and sensitivity to stimuli are two parameters that could, at least in part, account for bee tolerance to Varroa; differences in olfaction may be related to increased grooming and hygienic behavior, important behaviors known to be involved in Varroa tolerance.
Conclusion:
These results suggest that differences in behavior, rather than in the immune system, underlie Varroa tolerance in honey bees, and give an indication of the specific physiological changes found in parasitized bees. They provide a first step toward better understanding molecular pathways involved in this important host-parasite relationship.</description>
			<link>http://www.biomedcentral.com/1471-2164/9/301</link>		
			<dc:creator>M Navajas, A Migeon, C Alaux, ML Martin-Magniette, GE Robinson, JD Evans, S Cros-Arteil, D Crauser and Y Le Conte</dc:creator>
			<dc:source>BMC Genomics 2008, 9:301</dc:source>
			<dc:subject>Number of accesses: 714</dc:subject>
			<dc:date>2008-06-25</dc:date>
			<dc:identifier>doi:10.1186/1471-2164-9-301</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genomics</prism:publicationName>
					
			
							
					<prism:issn>1471-2164</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>301</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-06-25</prism:publicationDate>
					

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