91 resultados para GENE SET ANALYSIS


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This study demonstrated key resistance genes to fluroquinilones in Streptococcci isolated from sputum of people with CF. This suggests that other bacteria which are sometimes considered commensal may be a resovoir for resistance. Jse designed the study with Moore.

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Background: The availability of large-scale high-throughput data possesses considerable challenges toward their functional analysis. For this reason gene network inference methods gained considerable interest. However, our current knowledge, especially about the influence of the structure of a gene network on its inference, is limited.

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Erythrocytosis arises from a variety of pathogenic mechanisms. We sequenced a 256-bp region 3' to the erythropoietin (Epo) gene which included a 24- to 50-bp minimal hypoxia-responsive element spanning HIF-1- and HNF-4-binding sites in 12 patients with erythrocytosis and 4 normal subjects. Four polymorphisms were found, none of which affected the HIF-1-binding site, although one polymorphism was present in the HNF-4 consensus region. The data indicate that none of these polymorphisms cause erythrocytosis.

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The O-repeating unit of the Escherichia coli O7-specific lipopolysaccharide is made of galactose, mannose, rhamnose, 4-acetamido-4,6-dideoxyglucose, and N-acetyglucosamine. We have recently characterized the genes involved in the biosynthesis of the sugar precursor GDP-mannose occurring in the E. coli O7:K1 strain VW187 (C. L. Marolda and M. A. Valvano, J. Bacteriol. 175:148-158, 1993). In the present study, we identified and sequenced the rfbBDAC genes encoding the enzymes for the biosynthesis of another precursor, dTDP-rhamnose. These genes are localized on the upstream end of the rfbEcO7 region, and they are strongly conserved compared with similar genes found in various enteric and nonenteric bacteria. Upstream of rfbB we identified a DNA segment containing the rfb promoter and a highly conserved untranslated leader sequence also present in the promoter regions of other surface polysaccharide gene clusters. Also, we have determined that rfbB and rfbA have homologs, rffG (o355) and rffH (o292), respectively, located on the rff cluster, which is involved in the synthesis of enterobacterial common antigen. We provide biochemical evidence that rffG and rffH encode dTDP-glucose dehydratase and glucose-1-phosphate thymidylyltransferase activities, respectively, and we also show that rffG complemented the rfbB defect in the O7+ cosmid pJHCV32. We also demonstrate that rffG is distinct from rffE and map the rffE gene to the second gene of the rff cluster.

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Background:
The physical periphery of a biological cell is mainly described by signaling pathways which are triggered by transmembrane proteins and receptors that are sentinels to control the whole gene regulatory network of a cell. However, our current knowledge about the gene regulatory mechanisms that are governed by extracellular signals is severely limited.Results: The purpose of this paper is three fold. First, we infer a gene regulatory network from a large-scale B-cell lymphoma expression data set using the C3NET algorithm. Second, we provide a functional and structural analysis of the largest connected component of this network, revealing that this network component corresponds to the peripheral region of a cell. Third, we analyze the hierarchical organization of network components of the whole inferred B-cell gene regulatory network by introducing a new approach which exploits the variability within the data as well as the inferential characteristics of C3NET. As a result, we find a functional bisection of the network corresponding to different cellular components.

Conclusions:
Overall, our study allows to highlight the peripheral gene regulatory network of B-cells and shows that it is centered around hub transmembrane proteins located at the physical periphery of the cell. In addition, we identify a variety of novel pathological transmembrane proteins such as ion channel complexes and signaling receptors in B-cell lymphoma. © 2012 Simoes et al.; licensee BioMed Central Ltd.

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To investigate the association between polymorphisms of the aldose reductase gene and diabetic nephropathy in both Type 1 and Type 2 diabetes mellitus, and to carry out a meta-analysis of published results.

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Nematode parasites of the genus Trichinella are intracellular and distinct life cycle stages invade intestinal epithelial and skeletal muscle cells. Within the genus, Trichinella spiralis and Trichinella pseudospiralis exhibit species-specific differences with respect to host-parasite complex formation and host immune modulation. Parasite excretory-secretory (ES) proteins play important roles at the host-parasite interface and are thought to underpin these differences in biology. Serine proteases are among the most abundant group of T. spiralis ES proteins and multiple isoforms of the muscle larvae-specific TspSP-1 serine protease have been identified. Recently, a similar protein (TppSP-1) in T. pseudospiralis muscle larvae was identified. Here we report the cloning and characterisation of the full-length transcript of TppSP-1 and present comparative data between TspSP-1 and TppSP-1.

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The SH gene and its flanking sequences have been analysed for 10 strains of mumps virus (MuV) and compared to 5 others. A new lineage has been identified among UK isolates. Changes in the transcription pattern could not be correlated with differences in the sequences of the F-SH and SH-HN intergenic regions of the genome.

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High-dimensional gene expression data provide a rich source of information because they capture the expression level of genes in dynamic states that reflect the biological functioning of a cell. For this reason, such data are suitable to reveal systems related properties inside a cell, e.g., in order to elucidate molecular mechanisms of complex diseases like breast or prostate cancer. However, this is not only strongly dependent on the sample size and the correlation structure of a data set, but also on the statistical hypotheses tested. Many different approaches have been developed over the years to analyze gene expression data to (I) identify changes in single genes, (II) identify changes in gene sets or pathways, and (III) identify changes in the correlation structure in pathways. In this paper, we review statistical methods for all three types of approaches, including subtypes, in the context of cancer data and provide links to software implementations and tools and address also the general problem of multiple hypotheses testing. Further, we provide recommendations for the selection of such analysis methods.