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Littérature scientifique sur le sujet « Affymetrix gene chips »

Auteur : Grafiati
Publié le 4 juin 2021
Mis à jour le 6 février 2022

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Articles de revues sur le sujet "Affymetrix gene chips"

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Voss, Joachim G., Raghavan Raju, Carolea Logun, Robert L. Danner, Peter J. Munson, Zoila Rangel et Marinos C. Dalakas. « A Focused Microarray to Study Human Mitochondrial and Nuclear Gene Expression ». Biological Research For Nursing 9, no 4 (avril 2008) : 272–79. http://dx.doi.org/10.1177/1099800408315160.

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A focused microarray (huMITOchip) was developed to study alterations of human mitochondrial and nuclear gene expression in health and disease. The huMITOchip contains 4,774 probe sets identical to the Affymetrix U 133 plus 2.0 chip covering genes affecting mitochondrial, lipid, cytokine, apoptosis, and muscle function transcripts. Unlike other gene chips, the huMITOchip has 51 probe sets that interrogate 37 genes of the mitochondrial genome. The human mitochondrial gene chip was validated against the Affymetrix U133 plus 2.0 array using an in vitro system of CCL136 muscle cell line stimulated with or without interferon gamma (IFN-γ). The 37 genes from the mtDNA demonstrated absolute gene expression levels ranging from 0.1 to 3,182. The comparison of the two gene chips yielded an excellent Pearson's correlation coefficient ( r = 0.98). At least 17 probe sets were differentially expressed in response to IFN-γ on both chips, with a high degree of concordance. This is the first report on the development of a focused oligonucleotide microarray containing genes of the mitochondrial genome.
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Memon, Farhat Naureen, Graham J. G. Upton et Andrew P. Harrison. « A Comparative Study of the Impact of G-Stack Probes on Various Affymetrix GeneChips of Mammalia ». Journal of Nucleic Acids 2010 (2010) : 1–6. http://dx.doi.org/10.4061/2010/489736.

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We have previously discovered that probes containing runs of four or more contiguous guanines are not reliable for measuring gene expression in the Human HG_U133A Affymetrix GeneChip data. These probes are not correlated with other members of their probe set, but they are correlated with each other. We now extend our analysis to different3′GeneChip designs of mouse, rat, and human. We find that, in all these chip designs, the G-stack probes (probes with a run of exactly four consecutive guanines) are correlated highly with each other, indicating that such probes are not reliable measures of gene expression in mammalian studies. Furthermore, there is no specific position of G-stack where the correlation is highest in all the chips. We also find that the latest designs of rat and mouse chips have significantly fewer G-stack probes compared to their predecessors, whereas there has not been a similar reduction in G-stack density across the changes in human chips. Moreover, we find significant changes in RMA values (after removing G-stack probes) as the number of G-stack probes increases.
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Lauren, P. D. « Algorithm to model gene expression on affymetrix chips without the use of MM cells ». IEEE Transactions on Nanobioscience 2, no 3 (septembre 2003) : 163–70. http://dx.doi.org/10.1109/tnb.2003.817020.

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MARTIGNETTI, LOREDANA, ANDREI ZINOVYEV et EMMANUEL BARILLOT. « IDENTIFICATION OF SHORTENED 3′ UNTRANSLATED REGIONS FROM EXPRESSION ARRAYS ». Journal of Bioinformatics and Computational Biology 10, no 02 (avril 2012) : 1241001. http://dx.doi.org/10.1142/s0219720012410016.

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Cancer cells have been recently shown to express high level of short 3′UTR isoforms that can escape miRNA-mediated regulation. We present here a computational procedure for systematically identifying shortened 3′UTRs by Affymetrix 3′ microarrays. The advantage of this technology compared to more recent and promising ones such as exon arrays and RNA-Seq is that, giving the relatively small cost, already existing datasets in public databases include a considerably higher number of experiments. Moreover, the design of Affymetrix Gene Chips is well-suited for 3′UTR analysis of a large number of genes. Initially, Affymetrix individual probes are regrouped into customized probesets mapping specifically the CDS or the 3′UTR of the transcript, according to RefSeq annotation. Then, candidate 3′UTR shortening events are identified by statistical differential expression analysis of customized probesets in different biological conditions. The procedure has been applied to expression data from two ovarian adenocarcinoma datasets. Selected gene sets are significantly enriched for annotated splice variant genes as well as genes involved in estrogen dependent cancer mechanisms, confirming the validity of the proposed procedure.
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Fu, Li M., et Casey S. Fu-Liu. « The gene expression data of Mycobacterium tuberculosis based on Affymetrix gene chips provide insight into regulatory and hypothetical genes ». BMC Microbiology 7, no 1 (2007) : 37. http://dx.doi.org/10.1186/1471-2180-7-37.

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Boes, Tanja, Elisabeth Kruse, Johannes Hüsing et Karl-Heinz Jöckel. « P2.64 : Effects of the probeset expression measure computation of gene expression data derived from Affymetrix-Chips ». Biometrical Journal 46, S1 (mars 2004) : 153. http://dx.doi.org/10.1002/bimj.200490061.

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Dumur, Catherine I., Suhail Nasim, Al M. Best, Kellie J. Archer, Amy C. Ladd, Valeria R. Mas, David S. Wilkinson, Carleton T. Garrett et Andrea Ferreira-Gonzalez. « Evaluation of Quality-Control Criteria for Microarray Gene Expression Analysis ». Clinical Chemistry 50, no 11 (1 novembre 2004) : 1994–2002. http://dx.doi.org/10.1373/clinchem.2004.033225.

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Abstract Background: Development of quality-control criteria to ensure reproducibility of microarray results for potential clinical application is still in its infancy. Methods: In the present studies we developed quality-control criteria and evaluated their effect in microarray data analysis using total RNA from cell lines, frozen tumors, and a commercially available reference RNA. Quality-control criteria such as A260/A280 ratios, percentage of rRNA, and median size of cDNA and cRNA synthesis products were evaluated for robustness in microarray analysis. Furthermore, precision studies using a reference material were performed on the Affymetrix® HG-U133A high-density oligonucleotide microarrays. The same reference RNA sample was examined in 16 different chips run on 2 different days in the four different modules of the Affymetrix fluidics workstation. Fresh and frozen fragmented cRNAs were also compared. An ANOVA model was fit to identify the main sources of variation. Results: Good-quality samples showed >30% rRNA in the electropherograms and cDNA and cRNA synthesis products with median sizes of 2.0 and 3.0 kb, respectively. Precision studies showed that the main source of variation was the day-to-day variability, minimally affecting hybridization exogenous control genes. Altogether, the results showed that the Affymetrix Genechip® system is highly reproducible when RNA that meet the quality-control criteria are used (overall P >0.01). Conclusions: These results confirm the need to establish defined quality-control criteria for sample quality to distinguish between analytical and biological variability.
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Misson, J., K. G. Raghothama, A. Jain, J. Jouhet, M. A. Block, R. Bligny, P. Ortet et al. « A genome-wide transcriptional analysis using Arabidopsis thaliana Affymetrix gene chips determined plant responses to phosphate deprivation ». Proceedings of the National Academy of Sciences 102, no 33 (5 août 2005) : 11934–39. http://dx.doi.org/10.1073/pnas.0505266102.

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Jung, Sin-Ho, et Insuk Sohn. « Statistical Issues in the Design and Analysis of nCounter Projects ». Cancer Informatics 13s7 (janvier 2014) : CIN.S16343. http://dx.doi.org/10.4137/cin.s16343.

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Numerous statistical methods have been published for designing and analyzing microarray projects. Traditional genome-wide microarray platforms (such as Affymetrix, Illumina, and DASL) measure the expression level of tens of thousands genes. Since the sets of genes included in these array chips are selected by the manufacturers, the number of genes associated with a specific disease outcome is limited and a large portion of the genes are not associated. nCounter is a new technology by NanoString to measure the expression of a selected number (up to 800) of genes. The list of genes for nCounter chips can be selected by customers. Due to the limited number of genes and the price increase in the number of selected genes, the genes for nCounter chips are carefully selected among those discovered from previous studies, usually using traditional high-throughput platforms, and only a small number of definitely unassociated genes, called control genes, are included to standardize the overall expression level across different chips. Furthermore, nCounter chips measure the expression level of each gene using a counting observation while the traditional high-throughput platforms produce continuous observations. Due to these differences, some statistical methods developed for the design and analysis of high-throughput projects may need modification or may be inappropriate for nCounter projects. In this paper, we discuss statistical methods that can be used for designing and analyzing nCounter projects.
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Haerizadeh, Farzad, Mohan B. Singh et Prem L. Bhalla. « Transcriptome profiling of soybean root tips ». Functional Plant Biology 38, no 6 (2011) : 451. http://dx.doi.org/10.1071/fp10230.

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Soybean (Glycine max L.), a major legume crop, is important to human nutrition and is a source of animal feed. Similar to many legumes, a key feature of the soybean is its symbiotic association with soil bacteria that fix atmospheric nitrogen. However, knowledge of the gene expression of its root system, particularly the root meristematic region, is limited. Here, we have addressed this by investigating the gene expression profile of the soybean root tip, using soybean Affymetrix chips containing 37 500 probe sets (Affymetrix Inc.) and have compared this expression profile with that of the nonmeristematic tissue. We identified a total of 5012 upregulated and 4136 downregulated genes in the soybean root tip. Among the upregulated genes, 559 showed strong preferential expression in the root tip, indicating that they are likely to be associated with root apical meristem specificity and root tip function. Genes involved in membrane transport, defence signalling and metabolism were upregulated in the soybean root tip. Further, our data provide a resource of novel target genes for further studies involving root development and biology, and will possibly have a positive impact on future crop breeding.
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Thèses sur le sujet "Affymetrix gene chips"

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Alsabi, Qamar. « Characterizing Basal-Like Triple Negative Breast Cancer using Gene Expression Analysis : A Data Mining Approach ». Wright State University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=wright1578936915199438.

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Mořkovský, Libor. « Charakterizace genového obsahu chromosomu Z u ptáků ». Master's thesis, 2010. http://www.nusl.cz/ntk/nusl-296526.

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Theory predicts that sexually antagonistic mutations will be over- or under-represented on the X and Z chromosomes, depending on the average dominance coefficient of the mutations. However, as little is known about the dominance coefficients for new mutations, the effect of sexually antagonistic selection is difficult to predict. To elucidate the role of sexually antagonistic selection in the evolution of Z chromosome gene content in chicken, we analyzed publicly available microarray data from several somatic tissues as well as somatic and germ cells of the ovary. We found that the Z chromosome is enriched for genes showing preferential expression in ovarian somatic cells, but not for genes with preferential expression in primary oocytes or non-sex-specific somatic tissues. Our results suggest that sexual antagonism leads to higher abundance of female-benefit alleles on the Z chromosome. No bias towards Z-linkage of oocyte-enriched genes can be explained by lower intensity of sexually antagonistic selection in ovarian germ cells compared to ovarian somatic cells. An alternative explanation would be that meiotic Z chromosome inactivation hinders accumulation of oocyte-expressed genes on the Z chromosome. Our results are consistent with findings in mammals and indicate that recessive rather than dominant...
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Chapitres de livres sur le sujet "Affymetrix gene chips"

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Yang, Howard H., Nan Hu, Philip R. Taylor et Maxwell P. Lee. « Whole Genome-Wide Association Study Using Affymetrix SNP Chip : A Two-Stage Sequential Selection Method to Identify Genes That Increase the Risk of Developing Complex Diseases ». Dans Methods in Molecular Medicine™, 23–35. Totowa, NJ : Humana Press, 2008. http://dx.doi.org/10.1007/978-1-60327-148-6_2.

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Chen, Dung-Tsa, et James J. Chen. « MICROARRAY DATA ANALYSIS IN AFFYMETRIX GENE CHIP ». Dans Quantitative Medical Data Analysis Using Mathematical Tools and Statistical Techniques, 133–57. WORLD SCIENTIFIC, 2007. http://dx.doi.org/10.1142/9789812772121_0007.

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