... Thomas R. Gingeras, Affymetrix Inc., Santa Clara, CA. The first drafts of complete human genome sequence have brought with them the opportunities to map the RNA transcription patterns that are characteristic of each differentiated and undifferentiated cell type and characterize the sequence variations that underlie the phenotypic differences observed in the human population. By using the very high information content inherent in high-density oligonucleotide arrays it will be possible to map the locations of RNA transcription along the length of the entire human genome. Such a transcriptome map will provide information concerning: 1) the identification of novel transcription domains of the genome, 2) the predominant utilization of exon sequences during differentially spliced gene expression and 3) a empirically derived set of results which can be compared to the sequence annotation now being assembled ...
EMEA Oligonucleotide DNA Microarrays (oDNA) market analysis of an industry is a crucial thing for various stakeholders like investors, CEOs, traders, suppliers and others. The Oligonucleotide DNA Microarrays (oDNA) industry research report is a resource, which provides current as well as upcoming technical and financial details of the industry.. Oligonucleotide DNA Microarrays (oDNA) market 2017-2022 research report is a professional and in-depth study on the current state of this market. Various definitions and classification of the industry, applications of the industry and chain structure are given. Present day status of the Oligonucleotide DNA Microarrays (oDNA) industry policies and news are analysed.. Following are major Table of Content of Oligonucleotide DNA Microarrays (oDNA) Industry:. Oligonucleotide DNA Microarrays (oDNA) Market Competition by Manufacturers, Oligonucleotide DNA Microarrays (oDNA) Production, Revenue by Region, Oligonucleotide DNA Microarrays (oDNA) Supply, ...
TY - JOUR. T1 - DNA microarray-based identification of bacterial and fungal pathogens in bloodstream infections. AU - Yoo, Seung Min. AU - Choi, JunYong. AU - Yun, Jung Kuk. AU - Choi, Jae Kyung. AU - Shin, So Youn. AU - Lee, Kyungwon. AU - Kim, June Myung. AU - Lee, Sang Yup. PY - 2010/2/1. Y1 - 2010/2/1. N2 - The accurate and rapid identification of pathogens in blood is a major challenge in clinical pathogen diagnostics because of the high mortality of sepsis. Here we report the development of DNA microarray for the identification of pathogens causing bloodstream infections. Species-specific and bacteria- and fungi-broad-ranged probes were designed to identify 50 bacteria and 7 fungi. The specificities and sensitivities of the selected probes were successfully validated by applying reference strains. To assess the performance of the DNA microarray in a clinical setting, blind tests were performed using 112 blood culture specimens that showed preliminary presence of pathogenic microorganisms ...
The comparability of gene expression data generated with different microarray platforms is still a matter of concern. Here we address the performance and the overlap in the detection of differentially expressed genes for five different microarray platforms in a challenging biological context where differences in gene expression are few and subtle. Gene expression profiles in the hippocampus of five wild-type and five transgenic δC-doublecortin-like kinase mice were evaluated with five microarray platforms: Applied Biosystems, Affymetrix, Agilent, Illumina, LGTC home-spotted arrays. Using a fixed false discovery rate of 10% we detected surprising differences between the number of differentially expressed genes per platform. Four genes were selected by ABI, 130 by Affymetrix, 3,051 by Agilent, 54 by Illumina, and 13 by LGTC. Two genes were found significantly differentially expressed by all platforms and the four genes identified by the ABI platform were found by at least three other platforms.
High density oligonucleotide array technology is widely used in many areas of biomedical research for quantitative and highly parallel measurements of gene expression. Affymetrix GeneChip arrays are the most popular. In this technology each gene is typically represented by a set of 11-20 pairs of probes. In order to obtain expression measures it is necessary to summarize the probe level data. Using two extensive spike-in studies and a dilution study, we developed a set of tools for assessing the effectiveness of expression measures. We found that the performance of the current version of the default expression measure provided by Affymetrix Microarray Suite can be significantly improved by the use of probe level summaries derived from empirically motivated statistical models. In particular, improvements in the ability to detect differentially expressed genes are demonstrated ...
TY - JOUR. T1 - A Sequence Based Validation of Gene Expression Microarray Data. AU - Thallinger, Gerhard. AU - Obermayr, Eva. AU - Charoentong, Pornpimol. AU - Tong, Dan. AU - Trajanoski, Zlatko. AU - Zeillinger, Robert. PY - 2012. Y1 - 2012. UR - http://thescipub.com/ajb.toc. U2 - 10.3844/ajbsp.2012.1.9. DO - 10.3844/ajbsp.2012.1.9. M3 - Article. VL - 1. SP - 1. EP - 9. JO - American journal of bioinformatics. JF - American journal of bioinformatics. SN - 1948-9862. IS - 1. ER - ...
This example shows how to use MATLAB® and Bioinformatics Toolbox™ for preprocessing Affymetrix® oligonucleotide microarray probe-level data with two preprocessing techniques, Robust Multi-array Average (RMA) and GC Robust Multi-array Average (GCRMA).
contribute to the vascular remodeling process associated with hypertension and atherosclerosis, the aims of this study were to assess the impact of 2-ME on pathophysiological pathways regulating SMC growth using transcriptional profiling. High-density oligonucleotide microarrays (Affymetrix Human Genome U_133 Plus 2.0 GeneChips) were used to identify differentially expressed genes in cultured human aortic SMCs treated with 2-ME (acutely, for 4 hrs, n=3; and chronically, for 48 hrs, n=3) and vehicle-treated time-matched controls (n=3 for each time point). Both single gene analysis (performed using Significance Analysis of Microarrays) as well as Gene Set Enrichment Analysis (GSEA, a computational method that determines whether an a priori defined set of genes shows statistically significant, concordant differences between two biological states) indicated downregulation of genes critically involved in mitotic spindle assembly and function in SMCs chronically treated with 2-ME when compared to ...
This introductory course on microarray analysis is targeted to people without previous knowledge on this field. We will cover the basic steps that should be followed to obtain a list of differentially expressed genes, starting from raw expression data. The theoretical part of the course will be comprehensive and the similarities and differences between one- and two-color arrays will be discussed. For the practical part, an already published public dataset of Agilent two-color arrays will be used for all subsequent hands-on work. Students will get familiar with raw data format, background subtraction and normalization procedures that are needed before any differential expression analysis ...
With microarray technology, variability in experimental environments such as RNA sources, microarray production, or the use of different platforms, can cause bias. Such systematic differences present a substantial obstacle to the analysis of microarray data, resulting in inconsistent and unreliable information. Therefore, one of the most pressing challenges in the field of microarray technology is how to integrate results from different microarray experiments or combine data sets prior to the specific analysis. Two microarray data sets based on a 17k cDNA microarray system were used, consisting of 82 normal colon mucosa and 72 colorectal cancer tissues. Each data set was prepared from either total RNA or amplified mRNA, and the difference of RNA source between these two data sets was detected by ANOVA (Analysis of variance) model. A simple integration method was introduced which was based on the distributions of gene expression ratios among different microarray data sets. The method transformed gene
High density oligonucleotide microarrays are widely used in many areas of biological research for quantitative, high-throughput measurements of gene expression. Although ultra-deep sequencing techniques promise to replace them in the near future [1], it would be a mistake to ignore the biological importance of the massive quantity of data already produced through this platform. Publicly available databases alone store a huge (and growing) quantity of microarray experiments (e.g. 338947 samples in Gene Expression Omnibus [2] and 251711 in ArrayExpress [3]), comprising hundreds of different species.. Among microarrays, the single-channel Affymetrix GeneChip platform [4] is by far the most popular (for instance, in Gene Expression Omnibus they represent 97.9% of all arrays available for Arabidopsis thaliana, and 99.0% for Homo sapiens). In this technology each transcript is typically measured by a set of 11-20 pairs of 25 bases-long probes, collectively referred to as "probeset".. For every ...
Arrayit offers complete microarray services including microarray design, microarray sample preparation, microarray labeling, microarray amplification, microarray hybridization, microarray processing, microarray scanning, and microarray data analysis. Our high-throughput microarray cleanroom facilities enable a microarray service to meet the needs of every research laboratory, biotech, pharmaceutical company, hospitical and clinic. DNA microarrays, protein microarrays, peptide microarrays and VIP microarrays are included in our services offerings.
With the microarray technology rapidly advanced, tiling arrays have quickly become one of the most powerful tools in genome-wide investigations. High density tiling arrays [1] can be used to address many biological problems such as transcriptome mapping, protein-DNA interaction mapping (ChIP-chip) and array CGH among others [2]. ChIP-chip [3], the focus of the paper, is a technique that combines chromatin immunoprecipitation (ChIP) with microarray technology (chip). It allows efficient, scalable and comprehensive identification of binding sites and profiles of DNA-binding proteins [4]. High density ChIP-chip tiling arrays not only help us map the binding sites of a protein in the genome, but also allow us to better understand the binding events of the protein by clearly displaying the binding occupancy profiles. Several methods have been proposed to analyze the ChIP-chip data; for example, Joint Binding De-convolution (JBD) [5] uses a probabilistic graphical model to improve spatial resolution ...
CGH stands for comparative genome hybridisation, which aims to compare the presence / absence / number of similar genes in 2 genomes (i.e. its a survey of genetic differences between 2 organisms). So, a CGH experiment might compare gemomic DNA from 2 closely related bacterial species or strains. The difference between CGH array experiments and gene expression array experiments is just the target which is hybridised to the array: labelled genomic DNA for CGH; labelled cDNA (or cRNA - derived from mRNA in either case) for gene expression. You can use exactly the same arrays for both types of experiment, although the objective of CGH is normally genome-wide comparison of 2 genomes, so CGH normally uses whole-genome microarrays (for prokaryotes, at least). In general, you can use any genomic array for either gene expression or CGH ...
We performed a Nimblegen intra-platform microarray comparison by assessing two categories of flax target probes (short 25-mers oligonucleotides and long 60-mers oligonucleotides) in identical conditions of target production, design, labelling, hybridization, image analyses, and data filtering. We compared technical parameters of array hybridizations, precision and accuracy as well as specific gene expression profiles. Comparison of the hybridization quality, precision and accuracy of expression measurements, as well as an interpretation of differential gene expression in flax tissues were performed. Both array types yielded reproducible, accurate and comparable data that are coherent for expression measurements and identification of differentially expressed genes. 60-mers arrays gave higher hybridization efficiencies and therefore were more sensitive allowing the detection of a higher number of unigenes involved in the same biological process and/or belonging to the same multigene family. The two flax
Other. The DNA Microarray report does the thorough study of the key industry players to understand their business strategies, annual revenue, company profile and their contribution to the DNA Microarray market share in the United States. Diverse factors of the DNA Microarray industry like the supply chain scenario, industry standards, import/export details are also mentioned in this report.. Key Highlights of the United States DNA Microarray Market 2017 Report:. A Clear understanding of the DNA Microarray market based on growth, constraints, opportunities, feasibility study.. Concise DNA Microarray Market study based on major United States regions.. Analysis of evolving market segments as well as a complete study of existing DNA Microarray market segments.. Before Purchasing, Request Free Sample Copy of the Report Here: http://qyresearch.us/report/united-states-dna-microarray-market-2017/107122/#requestForSample. Furthermore, distinct aspects of DNA Microarray market like the technological ...
Microarrays have been useful in understanding various biological processes by allowing the simultaneous study of the expression of thousands of genes. However, the analysis of microarray data is a challenging task. One of the key problems in microarray analysis is the classification of unknown expression profiles. Specifically, the often large number of non-informative genes on the microarray adversely affects the performance and efficiency of classification algorithms. Furthermore, the skewed ratio of sample to variable poses a risk of overfitting. Thus, in this context, feature selection methods become crucial to select relevant genes and, hence, improve classification accuracy. In this study, we investigated feature selection methods based on gene expression profiles and protein interactions. We found that in our setup, the addition of protein interaction information did not contribute to any significant improvement of the classification results. Furthermore, we developed a novel feature ...
A literature search for non-uniform distributions of P values shows few citations [3, 5] and these both relate to statistical tests applied to expression results generated using Affymetrix microarrays. Huang et al. [5] compare gene expression profiles of tumours in three groups of mice using an Affymetrix Mouse Genechip array. When an ANOVA was performed on the expression of around 23,000 genes, a distribution of P values similar to Figure 1 was obtained. However when a t-test was applied to 2 of these groups, a distribution of P values similar to Figure 3 was obtained. The authors hypothesised that the reason for such a non-uniform distribution was due to excess biological similarity between some samples in the groups used for the t-test. This excess biological similarity was thought to be due to 2 pairs of samples being littermates of the same age and a further 2 pairs of samples were assayed at the same time. This resulted in the samples used for the t-test not being statistically ...
Microarray technology is a powerful tool for genomic analysis. It gives a global view of the genome in a single experiment. Data analysis of the microarray is a vital part of the experiment. Each microarray study comprises multiple microarrays, each giving tens of thousands of data points. Since the volume of data is growing exponentially as microarrays grow larger, the analysis becomes more challenging. In general the greater the volume of data, the more chances arise for erroneous results. Handling such large volumes of data requires high-end computational infrastructures and programs that can handle multiple data formats. There are already programs available for microarray data analysis on various platforms. However, due to rapid development, diversity in microarray technology, and different data formats, there is always the need for more comprehensive and complete microarray data analysis. Proper data processing and quality control are critical to the validity and interpretability of gene ...
Apolipoprotein O (apoO) is a new member of the apolipoprotein family. However, data on its physiological functions are limited and inconsistent. Using a microarray expression analysis, this study explored the function of apoO in liver cells. HepG2 cells were treated either with oleic acid or tumor necrosis factor-α for 24 h. mRNA and protein expression of apoO were assessed by quantitative real-time PCR (qRT-PCR) and Western blot respectively. An efficient lentiviral siRNA vector targeting the human apoO gene was designed and constructed. The gene expression profile of HepG2 human hepatocellular carcinoma cells transfected with the apoO silencing vector was investigated using a whole-genome oligonucleotide microarray. The expression levels of some altered genes were validated using qRT-PCR. ApoO expression in HepG2 cells was dramatically affected by lipid and inflammatory stimuli. A total of 282 differentially expressed genes in apoO-silenced HepG2 cells were identified by microarray analysis. These
immune Uncategorized 155294-62-5 IC50, Rabbit Polyclonal to SNX4. We have assessed the tool of RNA titration examples for evaluating microarray system functionality and the influence of different normalization methods over the outcomes obtained. widespread make use of, many locally are concerned using the comparability from the outcomes attained using different microarray systems and therefore the natural relevance from the qualitative and quantitative outcomes obtained. Microarray system functionality has been examined before over the requirements of awareness, specificity, powerful range, accuracy1C12 and precision. Within the MicroArray Quality Control (MAQC) task, very similar assessments have already been reported13 also,14. Other research have used described mixtures of RNA examples (titration examples) for interplatform2,15 and interlaboratory15 evaluations. Here weve investigated an alternative solution functionality metric: the talents of different microarray systems to accurately ...
Microarrays provided a practical method for measuring the expression of thousand of genes simultaneously. Although next generation sequencing has mainly replaced these assays, there is still a large amount of data available in public databases, that would enable to better design sequencing experiment with the insight of an high-throughput gene expression screening. For this reasons methods that have been developed in the past to analyse microarrays gene expression data, are still a valuable resource. Microarray technology is associated with many significant sources of experimental uncertainty, which must be considered in order to make confident inference from the data. Estimate of uncertainty is not entirely achieved using repeat experiments. Outliers are often due to flaws in the microarray technique or to problems in the hybridization of the biological material. In high-density oligonucleotide arrays as well as in cDNA spotted arrays the aim is to extract from pixel intensity signals an ...
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BACKGROUND: Illumina Infinium whole genome genotyping (WGG) arrays are increasingly being applied in cancer genomics to study gene copy number alterations and allele-specific aberrations such as loss-of-heterozygosity (LOH). Methods developed for normalization of WGG arrays have mostly focused on diploid, normal samples. However, for cancer samples genomic aberrations may confound normalization and data interpretation. Therefore, we examined the effects of the conventionally used normalization method for Illumina Infinium arrays when applied to cancer samples. RESULTS: We demonstrate an asymmetry in the detection of the two alleles for each SNP, which deleteriously influences both allelic proportions and copy number estimates. The asymmetry is caused by a remaining bias between the two dyes used in the Infinium II assay after using the normalization method in Illuminas proprietary software (BeadStudio). We propose a quantile normalization strategy for correction of this dye bias. We tested the ...
TY - JOUR. T1 - Identification of cell surface marker candidates on SV-T2 cells using DNA microarray on DLC-coated glass. AU - Tuoya, AU - Hirayama, Koichi. AU - Nagaoka, Tadahiro. AU - Yu, Dongwei. AU - Fukuda, Takayuki. AU - Tada, Hiroko. AU - Yamada, Hidenori. AU - Seno, Masaharu. PY - 2005/8/19. Y1 - 2005/8/19. N2 - We analyzed gene expression profiles of normal mouse fibroblast BALB/c 3T3 cells and its SV40 transformant SV-T2 cells using our originally developed cell surface marker DNA microarray, which is prepared on a diamond-like carbon-coated glass. As a result, CD62L and IL-6 receptor α gene expressions were upregulated in SV-T2 and were thought to be candidates for cell surface markers of the cells. The result of microarray analysis was validated by real-time quantitative PCR, immunohistochemistry and biological assays. These data show that our cell surface marker DNA microarray should be useful in finding the candidates of cell type-specific surface markers.. AB - We analyzed gene ...
The well-defined differences in metastatic behavior and the clonal relationship of the K7M2 and K12 cells allowed the use of cDNA microarrays to define potentially important genetic determinants for pulmonary metastasis in this model. Recently, cDNA microarray technology has been used to list genes that are differentially expressed between high and low metastatic tumor systems (18, 19, 20) . Data generated in such cDNA microarray comparisons are of considerable value; however, it is difficult to determine how best to use this information. Both traditional reductionist and novel bio-informatic approaches (including hierarchical cluster analyses) have been used to manage microarray data. In the cDNA microarray comparisons presented herein, we identified 53 genes that were differentially expressed between the high (K7M2) and the low (K12) metastatic OSA primary tumors. To use this information, we used a reductionist approach that was based on biological differences demonstrated between the high and ...
and Shahdara. Gene expression markers (GEMs) are based on differences in transcript levels that exhibit bimodal distributions in segregating progeny, while single feature polymorphism (SFP) markers rely on differences in hybridization to individual oligonucleotide probes. Unlike SFPs, GEMs can be derived from any type of DNA-based expression microarray. Our method identifies SFPs independent of a genes expression level. Alleles for each GEM and SFP marker were ascertained with GeneChip data from parental accessions as well as RILs; a novel algorithm for allele determination using RIL distributions capitalized on the high level of genetic replication per locus. GEMs and SFP markers provided robust markers in 187 and 968 genes, respectively, which allowed estimation of gene order consistent with that predicted from the Col-0 genomic sequence. Using microarrays on a population to simultaneously measure gene expression variation and obtain genotypic data for a linkage map will facilitate expression ...
Adjusting background for chip # 1 of 42 using MLE method. Adjusting background for chip # 2 of 42 using MLE method. Adjusting background for chip # 3 of 42 using MLE method. Adjusting background for chip # 4 of 42 using MLE method. Adjusting background for chip # 5 of 42 using MLE method. Adjusting background for chip # 6 of 42 using MLE method. Adjusting background for chip # 7 of 42 using MLE method. Adjusting background for chip # 8 of 42 using MLE method. Adjusting background for chip # 9 of 42 using MLE method. Adjusting background for chip # 10 of 42 using MLE method. Adjusting background for chip # 11 of 42 using MLE method. Adjusting background for chip # 12 of 42 using MLE method. Adjusting background for chip # 13 of 42 using MLE method. Adjusting background for chip # 14 of 42 using MLE method. Adjusting background for chip # 15 of 42 using MLE method. Adjusting background for chip # 16 of 42 using MLE method. Adjusting background for chip # 17 of 42 using MLE method. Adjusting ...
Researchers use DNA microarrays, or gene chips, to distinguish among different types of tissues based on the expression patterns of thousands of genes. A new study says the technology can be modified to profile more tissue samples simultaneously and with greater efficiency. The innovation is called an array of arrays. Gene expression profiles are typically obtained one at a time by hybridizing a single tissue sample to a single array on an individual glass slide. The integrated device described in the study is a glass wafer that includes 49 individual oligonucleotide arrays arranged as a 7 × 7 array of arrays. David J. Lockhart and colleagues at the Genomics Institute of the Novartis Research Foundation, in San Diego, California, developed a way to hybridize many tissue samples to multiple arrays on a single glass slide, or wafer. Using this and other modifications, they completed a study of gene expression in ovarian cancer in a single experiment. This was done in a fraction of the time and ...
Background Reproducibility is a fundamental requirement in scientific experiments. Some recent publications have claimed that microarrays are unreliable because lists of differentially expressed genes (DEGs) are not reproducible in similar experiments. Meanwhile, new statistical methods for identifying DEGs continue to appear in the scientific literature. The resultant variety of existing and emerging methods exacerbates confusion and continuing debate in the microarray community on the appropriate choice of methods for identifying reliable DEG lists. Results Using the data sets generated by the MicroArray Quality Control (MAQC) project, we investigated the impact on the reproducibility of DEG lists of a few widely used gene selection procedures. We present comprehensive results from inter-site comparisons using the same microarray platform, cross-platform comparisons using multiple microarray platforms, and comparisons between microarray results and those from TaqMan - the widely regarded ...
1567 With microarray data we successfully developed a novel system for predicting early intrahepatic recurrence of hepatocellular carcinoma (HCC) [1]. The HCC microarray data consists of 60 HCC patients with high-density oligonucleotide microarrays representing approximately 6000 genes. In this data, the 20 patients had early intrahepatic recurrence within 1 year after curative surgery and 40 patients had nonrecurrence. We randomly divided 60 samples into 33 training samples and 27 blinded samples. With 33 training samples, we selected 12 genes useful for prediction. In general, visualization of high-dimensional space is important to evaluate interactively genes and to elucidate mechanism of recurrence. The Karhunen-Loeve (KL) expansion [2], which corresponds to PCA, and the Sammons nonlinear mapping (SNM) [3], which corresponds to MDS, are popular visualization methods. We call these methods unsupervised visualization where labeled samples are not used. In this paper we propose visualization ...
Background: Unexpected phenotypes resulting from morpholino-mediated translational knockdown of Pitx3 in Xenopus laevis required further investigation regarding the genetic networks in which the gene might play a role. Microarray analysis was, therefore, used to assess global transcriptional changes downstream of Pitx3. Results: From the large data set generated, selected candidate genes were confirmed by reverse transcriptase-polymerase chain reaction (RT-PCR) and in situ hybridization. Conclusions: We have identified four genes as likely direct targets of Pitx3 action: Pax6, beta Crystallin-b1 (Crybb1), Hes7.1, and Hes4. Four others show equivocal promise worthy of consideration: Vent2, and Ripply2 (aka Ledgerline or Stripy), eFGF and RXRa. We also describe the expression pattern of additional and novel genes that are Pitx3-sensitive but that are unlikely to be direct targets.
RNA binding to high-density oligonucleotide arrays has shown tantalizing differences with solution experiments. We analyze here its sequence specificity, fitting binding affinities to sequence composition in large datasets. Our results suggest that the fluorescent labels interfere with binding, causing a catch-22. To be detected, the RNA must both glow and bind: without labels it cannot be seen even if bound, while with too many it will not bind. A simple model for the binding of labeled oligonucleotides sheds light on the interplay between binding energies and labeling probability.. Note: Comment in: Phys Rev E Stat Nonlin Soft Matter Phys. 2006 Jun;73(6 Pt 1):063901; author reply 063902. ...
Affymetrix® Microarrays Platform (PAM) is a service focused on DNA and RNA microarray solutions offered by Affymetrix, with the main goal to offer solutions towards a personalized medicine. We offer microarrays for expression and for cytogenetics studies, from the basic research to applied research and diagnosis.PAM is an Affymetrix European Reference Group for Cytogenetic
We have used oligonucleotide arrays to study the changes in mRNA expression after stimulation of the human HT1080 cell line with different IFNs. The effectiveness of this approach was evident by the ability to successfully identify and quantify the mRNA levels for many known ISGs. Previous Northern blot analyses of HT1080 cells showed that while IFN-α induced 6-16 mRNA levels by more than 20-fold, there was no detectable induction by IFN-γ; also, 9-27 mRNA levels were induced by both IFN-α and IFN-γ, although the level of 9-27 induction by IFN-α was 3-fold higher than by IFN-γ (5). These characteristics were replicated with remarkable similarity by the oligonucleotide arrays: 6-16 was absent in untreated cells and induced at least 20- and 21-fold by IFN-α or IFN-β, respectively, but not by IFN-γ; 9-27 was induced 23- and 22-fold by IFN-α or IFN-β and 8-fold by IFN-γ (Fig. 1 and Table 2). The consistency between our data and previous studies regarding IFN-specific inducibility further ...
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Background Although microarrays are analysis tools in biomedical research, they are known to yield noisy output that usually requires experimental confirmation. To tackle this problem, many studies have developed rules for optimizing probe design and devised complex statistical tools to analyze the output. However, less emphasis has been placed on systematically identifying the noise component as part of the experimental procedure. One source of noise is the variance in probe binding, which can be assessed by replicating array probes. The second source is poor probe performance, which can be assessed by calibrating the array based on a dilution series of target molecules. Using model experiments for copy number variation and gene expression measurements, we investigate here a revised design for microarray experiments that addresses both of these sources of variance. Results Two custom arrays were used to evaluate the revised design: one based on 25 mer probes from an Affymetrix design and the other
The barley (Hordeum vulgare) brittle stem mutants, fs2, designated X054 and M245, have reduced levels of crystalline cellulose compared with their parental lines Ohichi and Shiroseto. A custom-designed microarray, based on long oligonucleotide technology and including genes involved in cell wall metabolism, revealed that transcript levels of very few genes were altered in the elongation zone of stem internodes, but these included a marked decrease in mRNA for the HvCesA4 cellulose synthase gene of both mutants. In contrast, the abundance of several hundred transcripts changed in the upper, maturation zones of stem internodes, which presumably reflected pleiotropic responses to a weakened cell wall that resulted from the primary genetic lesion. Sequencing of the HvCesA4 genes revealed the presence of a 964-bp solo long terminal repeat of a Copia-like retroelement in the first intron of the HvCesA4 genes of both mutant lines. The retroelement appears to interfere with transcription of the HvCesA4 ...
... ,These extended-length microarrays are custom designed to meet your needs. Two probe density format configurations are available: 8,455 features per array (2 arrays/1 x 3 glass slide) or 22,575 features per array (1 array/slide).,biological,biology supply,biology supplies,biology product
Affymetrix Genechip® arrays are currently among the mostwidely used high-throughput technologies for the genome-widemeasurement of expression profiles. To minimize mis- and cross-hybridizationproblems, this technology includes both perfect match (PM) andmismatch (MM) probe pairs as well as multiple probes per gene(Lipshutz et al., 1999). As a result, significant preprocessingis required before an absolute expression level for a specificgene may be accurately assessed. Such data preprocessing steps-whichcombine multiple probe signals into a single absolute call-areknown as normalization procedures. They usually involve threesteps: (a) background adjustment, (b) normalization and (c)summarization (Gautier et al., 2004). Various methods have beendevised for each of the three steps and thus a great numberof possible combinations exist, facing the microarray user communitywith a complex and often daunting set of choices. We summarizesome of the commonly used procedures in Table 1. As more and more ...
CiteSeerX - Scientific documents that cite the following paper: Assessing gene significance from cDNA microarray expression data via mixed models.
A package that assesses RNA quality of Affymetrix expression data. The AffyRNADegradation package extends the Bioconductor package affy and integrates well in a typical microarray analysis workflow. All calculations are performed directly on the AffyBatch object and carried out separately for each particular microarray hybridization in a single-chip approach. Our approach corrects the 3′/5′-bias on the level of raw probe intensities, which can afterward be processed with any method. The runtime is about 2 min and 3 min per sample for index and distance based corrections, respectively. Because each chip is processed independently, arbitrarily large data sets can be processed.
New Zealand obese (NZO) mice exhibit severe insulin resistance of hepatic glucose metabolism. In order to define its biochemical basis, we studied the differential expression of genes involved in hepatic glucose and lipid metabolism by microarray analysis. NZOxF1 (SJLxNZO) backcross mice were generated in order to obtain populations with heterogeneous metabolism but comparable genetic background. In these backcross mice, groups of controls (normoglycemic/normoinsulinemic), insulin-resistant (normoglycemic/hyperinsulinemic) and diabetic (hyperglycemic/hypoinsulinemic) mice were identified. At 22 weeks, mRNA was isolated from liver, converted to cDNA, and used for screening of two types of cDNA arrays (high-density filter arrays and Affymetrix oligonucleotide microarrays). Differential gene expression was ascertained and assessed by Northern blotting. The data indicate that hyperinsulinemia in the NZO mouse is associated with: (i) increased mRNA levels of enzymes involved in lipid synthesis (fatty ...
BACKGROUND Complementary DNA array analysis of gene expression has a potential application for clinical diagnosis of disease processes. However, accessibility, affordability, reproducibility of results, and management of the data generated remain issues of concern. Use of cDNA arrays tailored for studies of specific pathways, tissues, or disease states may render a cost- and time-effective method to define potential hallmark genotype alterations. MATERIALS AND METHODS We produced a 332-membered human cDNA array on nylon membranes tailored for studies of angiogenesis and tumorigenesis in reproductive disease. We tested the system for reproducibility using a novel statistical approach for analysis of array data and employed the arrays to investigate gene expression alterations in ovarian cancer. RESULTS Intra-assay analysis and removal of agreement outliers was shown to be a critical step prior to interpretation of cDNA array data. The system revealed highly reproducible results, with intermembrane
Molecular diagnostics offer the promise of precise, objective, and systematic human cancer classification, the researchers write. But they caution that such tests cannot yet be used widely because characteristic molecular markers for most solid tumors have yet to be identified.. To lay the groundwork for their cancer diagnosis project, the researchers created a gene expression database that included profiles of the tumor samples. They used oligonucleotide microarrays glass slides spotted with genes of known functions containing 16,063 genes. Employing two different techniques clustering and training the scientists then analyzed the data and classified the tumors.. The researchers think that analyzing such genetic signatures can be important in troublesome diagnoses because molecular characteristics of a tumor sample may remain intact despite atypical clinical or histological features. However, they concede that such molecular tools are not a substitute for traditional diagnostics, ...
Event: | Partek Microarray and NGS Analysis WorkshopDate: April 1, 2014Cost: FreeCategory: TrainingContact: PARTEKEmail: [email protected]: March 19, 2014Venue: Multimedia training room 3.142, Queensland Bioscience PrecinctAddress: Building 80, The University of Queensland, 306 Carmody Rd, St Lucia, QLD, 4072, Australia This Partek Microarray and NGS Analysis Workshop is co-sponsored by QFAB.AGENDA 9:30 a.m. - 11:00 a.m. Microarray Gene Expression Analysis with Partek® Genomics Suite™ and Partek® Pathway™ 11:15 a.m. - 12:30 p.m. Sequence Alignment, QAQC, and RNA-Seq with Partek® Flow® 1:30 p.m. - 3:00 p.m. RNA-Seq Analysis with with Partek Genomics Suite 3:30 p.m. - 5:00 p.m. Variant Detection with Partek Genomics Suite Please click here to register to the Partek Workshop
We proposed an effective algorithm to analyze the periodicity of noisy microarray time series data. Each DNA microarray chip produces thousands of gene expressions. The data have a high level of noise, which make it a challenge to
A number of methods have been used to compare the absolute or relative expression of genes in two or more specimens. These include S.A.G.E. (Serial Analysis of Gene Expression), differential display, cDNA and oligonucleotide microarrays, and other methods. The Microarray Core offers a gene expression profiling service that uses oligonucleotide microarrays. Using this method, the RNA of interest is converted into cDNA, then amplified and labeled with biotinylated nucleotides by in vitro transcription to produce biotinylated cRNA. The cRNA is hybridized to a microarray chip. The bound cRNA is stained with fluorescent streptavidin. The microarray chip is then scanned using a laser, and the positions and intensities of the fluorescent emissions are captured. These measurements provide the basis of subsequent biostatistical analysis." ...
The advent of high-throughput technologies brought the opportunity for researchers to investigate and assess biological variability at the genomic level, but it also introduced unwanted technical variability that can cause perceived differences between samples processed on high-throughput technologies, irrespective of the biological variation. These differences may be due to differences in the way the samples were processed (such as batch effects) or to platform-dependent technical variation. Because global changes in distributions between groups can be caused by both technical variation and biological variation, it is important to note that our test statistic F quantro will detect global differences caused by both technical variation (e.g., batch effects) and biological variation. Data alone cannot determine if global changes are caused by technical variation or biological variation (Fig. 2), but quantro offers researchers a new tool to detect when there are global changes in distributions ...
The results of the different analytical approaches applied by the participating groups showed, in general, that the biological interpretation is highly dependent on the statistical method used.. The analysis for enrichment of GO-terms based on singular enrichment analysis (SEA), applied by the different groups (Table 2), revealed differences in numbers and identity of the GO-terms found to be affected. In general, many of the enriched GO-terms were found to be represented by few (1 or 2) genes. Applying the commonly used filtering criteria, requiring a reasonable number of genes, e.g. 10, to represent each GO-term, would lead to the conclusion that very few GO-terms are affected.. The commercial software Ingenuity Pathway Analysis (IPA) was used by the groups from University of Cordoba, Spain [25] and from INRA, Toulouse and Rennes [26] to explore the affected pathways. The results obtained by the two groups are quite similar even though the analyses were performed in different ways. In contrast ...
The transcription factor Grainy head (Grh) is conserved from Drosophila to humans. Drosophila Grh plays important roles in epithelial differentiation and regeneration. To investigate the mechanisms of Grh function, we performed ChIP-sequencing and microarray gene expression analysis and identified Grh target genes in Drosophila embryos at a genome-wide scale. We found Grh ChIP peaks in the proximity of 3754 genes and showed that Grh acts both as an activator and as a repressor. Grh regulates distinct genes in different contexts. During wound healing, Grh transcriptionally activates stitcher (stit), a gene encoding a receptor tyrosine kinase. We show that Stit activates two distinct pathways, including Src kinases and extracellular signal-regulated kinase (ERK), after injury. The tyrosine residue Y762 mediates Stit binding to the SH2 domains of Src42A, Src64B, or Drk. Src family kinases and Drk act as downstream effectors of Stit in the activation of wound response enhancers. Src family kinases ...
OBJECTIVE: To examine whether DNA microarray analysis of chromosomal susceptibility regions for allergy can help to identify candidate genes. MATERIAL AND METHODS: Nasal biopsies were obtained from 23 patients with allergic rhinitis and 12 healthy controls. RNA was extracted from the biopsies and pooled into three patient and three control pools. These were then analysed in duplicate with DNA microarrays containing 12626 genes. Candidate genes were further examined in nasal biopsies (real-time polymerase chain reaction) and blood samples (single nucleotide polymorphisms) from other patients with allergic rhinitis and from controls. RESULTS: A total of 37 differentially expressed genes were identified according to criteria involving both the size and consistency of the gene expression levels. The chromosomal location of these genes was compared with the chromosomal susceptibility regions for allergic disease. Using a statistical method, five genes were identified in these regions, including serine
Our goal is to assist in the grant development, publication writing, planning, analysis, and interpretation of DNA microarray data for UAB investigators. We strive to provide the most statistically valid and reliable results and interpretation possible. We aim to increase the number of high quality DNA microarray publications being authored by UAB investigators, to increase the funding for microarray experimentation, and make UAB a leader in the use of microarrays to advance scientific goals and increase our understanding of human health ...
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While there has been a proliferation in interest surrounding mucin production in IPF, the importance of cilia has received much less attention. The fascinating gene expression study from Yang et al6 in this edition of Thorax seems set to change this. The authors performed comparative RNA microarray analysis on lung tissue from 119 patients with well-characterised IPF and from patients with brain death whose lungs were considered unusable for lung transplantation. Genes differentially expressed in IPF were interrogated using hierarchical clustering, yielding two subgroups of IPF differentiated by distinct expression profiles. Intriguingly, the strongest signal distinguishing the two cohorts of patients with IPF appeared to come from cilia-associated genes and their structural components (DNAH6, DNAH7, DNAI1 and RPGRIP1L) as well as MUC5B. The authors broadly replicated their findings in lung tissue from an independent cohort with IPF. Interestingly, the two IPF cohorts were indistinguishable ...
ANSWER: A microarray database is a repository containing microarray gene expression data. The key uses of a microarray database are to store the measurement data, manage a searchable index, and make the data available to other applications for analysis and interpretation (either directly, or via
Background Affymetrix GeneChips? are an important tool in many facets of biological study. 80% of the content within the HuEx arrays is usually indicated at or near background. Biological variance seems to have a smaller effect on U133 data. Comparing the overlap of differentially indicated genes, we see a high overall concordance among all 3 platforms, with HuEx and HuGene having higher overlap, as expected given their design. We performed an analysis of detection rates and area under ROC curves using an experiment made up of a number of mixtures of 2 human being tissues. Though it appears that the HuEx array offers buy Refametinib worse performance in terms of detection rates, all arrays have similar ability to separate differentially indicated and non-differentially indicated genes. Conclusion Despite apparent variations in the probe-level reproducibility, gene-level reproducibility and differential manifestation detection are quite similar across the three platforms. The HuEx array, an ...
With the chip array technology, one can measure the expression of all genes at once (even all exons). Can answer questions such as: 1.Which genes are expressed in a muscle cell? 2.Which genes are expressed during the first weak of pregnancy in the mother? In the new baby? 3.Which genes are expressed in cancer?
A mouse model of acute lung injury (ALI) was chosen in this study to explore the key genes and pathways involved in the process of ALI with microarray technology. Gene expression microarray data were downloaded from the Gene Expression Omnibus database. Mice from the experimental group were further divided into 6 subgroups, which received octadecenoate treatments for 1, 1.5, 3, 4, 18, and 24 h. Differentially co-expressed genes were screened to uncover the pathogenesis of ALI. Almost all of the differentially co-expressed genes were identified at two times: 1.5 and 3 h. ...
Array hybridization devices and methods for their use are provided. The subject devices are characterized by having a substantially planar bottom surface, a cover, at least one fluid port and at least one adjustable spacing element for adjusting the spacing between an array and the bottom surface. In using the subject devices, an array is placed on the at least one adjustable spacing element in the chamber and the space between the array and the bottom surface is adjusted by moving the at least one adjustable spacing element. The adjusted array is contacted with at least one biological sample introduced into the chamber. The subject inventions find use in a variety of array-based applications, including nucleic acid array hybridizations.
Once the TVCs stop migrating, they undergo stereotyped rounds of asymmetric cell divisions which distinguish two types of muscle precursors: the heart and the atrial siphon muscles (ASM) precursors. Notably, the ASM precursors undergo a second polarized collective cell migration towards the dorsal atrial siphon placode. Shortly after they are born, the ASM start expressing genes encoding theDNA binding transcription factors COE and Islet. We found that COE function is necessary and sufficient to inhibit heart specification and impose the ASM fate, including migration towards the atrial placode. We are now using a combination of cis-regulatory analyses, candidate gene approach, cell sorting and whole genome microarray analyses to understand the mechanisms of ASM vs. heart fate specification and ASM migration. We are very interested in comparing the transcription profiles of migrating TVCs and ASMs inasmuch as they both undergo collective cell migration and arise from the same lineage, while there ...
To develop molecular-targeting anticancer drugs that are expected to be highly specific to malignant cells, with minimal risk of adverse reactions, we established an effective screening system to identify proteins that were activated specifically in lung cancers. First, we analyzed a genome-wide expression profile of 120 lung cancer samples through the genome-wide cDNA microarray system containing 27,648 genes coupled with cancer cell purification by laser microdissection (6-10). After verification of very low or absent expression of such genes in normal organs by cDNA microarray analysis and multiple-tissue Northern blot analysis, we analyzed the protein expression of candidate targets among hundreds of clinical samples on tissue microarrays, investigated loss of function phenotypes using RNA interference systems, and further defined biological functions of the proteins. Through these analyses, we identified candidate genes for the development of novel serum biomarkers (30-35), therapeutic ...
The repressor-activator protein 1 (Rap1) binds to [C(1-3)A]n repeats, acts as a transcriptional activator, and represses gene expression at telomeres by binding to the accessory silencing proteins Sir2, Sir3 and Sir4. In the Advance Online Publication of Nature Genetics, Lieb and colleagues, at Stanford University, describe a study to investigate the genome-wide DNA-binding specificity of Rap1 and Sir proteins in vivo (Nature Genetics 2001 DOI:10.1038/ng569). They performed chromatin immunoprecipitation (IP) experiments, followed by whole genome microarray analysis to map protein-DNA interactions (for Rap1, Sir2, Sir3 and Sir4) at a resolution of 2 kb. Rap1 binding localized to 294 loci (representing 5.4% of all yeast genes). Half of the Rap1-binding sites mapped to telomeric regions. Lieb et al. identified 362 ORFs that are adjacent to intergenic Rap1-binding loci. These included known Rap1 targets such as ribosomal protein genes and genes encoding glycolysis enzymes. They identified 185 ORFs ...
Gene expression can be quantitatively analyzed by hybridizing fluor-tagged mRNA to targets on a cDNA micro-array. Comparison of gene expression levels arising from co-hybridized samples is achieved by taking ratios of average expression levels for individual genes. In an image-processing phase, a method of image segmentation identifies cDNA target sites in a cDNA micro-array image. The resulting cDNA target sites are analyzed based on a hypothesis test and confidence interval to quantify the significance of observed differences in expression ratios. In particular, the probability density of the ratio and the maximum-likelihood estimator for the distribution are derived, and an iterative procedure for signal calibration is developed.
Purpose: This study aimed to identify a novel biomarker or a target of treatmentfor colorectal cancer (CRC). Experimental design: The expression profiles of cancer cells in 104 patients with CRC were examined using laser microdissection and oligonucleotide microarray analysis. Overexpression in CRC cells, especially in patients with distant metastases, was a prerequisite to select candidate genes. The mRNA expression of candidate genes was investigated by quantitative reverse transcription polymerase chain reaction (RT-PCR) in 77 patientsas a validation study. We analyzed the protein expression and localization of the candidate gene by immunohistochemical study and investigated the relationship between protein expression and clinicopathologic features in 274 CRC patients. Results: Using microarray analysis, we identified six candidate genes related to distant metastases in CRC patients. Among these genes, osteoprotegerin (OPG)is known to be associated with aggressiveness in several cancers ...
Affymetrix GeneChip Mapping assays require restriction sites for the digestion with enzymes. Due to the procedure of random DNA ligation when using the REPLI-g FFPE Kit, original restriction sites may be lost. Therefore, we do not recommend this kit in combination with the Affymetrix GeneChip procedure.. Affymetrix Targeted Genotyping assays on the other hand use a primer extension protocol and should be compatible with the REPLI-g FFPE procedure as they are not affected by the random ligation process.. ...
As promised a few posts ago, another demonstration of the excellent biomaRt package, this time in conjunction with GenomeGraphs. Heres what were going to do: Grab some public microarray data Normalise and get a list of the most differentially-expressed probesets Use biomaRt to fetch the genes associated with those probesets Plot the data using GenomeGraphs…
The biological landscape has been transformed by the sequencing of genomes, and more recently by global gene expression analyses using microarrays [1, 2]. Microarrays contain DNA probes representing all coding sequences in a genome, which are either synthesized in situ or are spotted onto a modified glass surface [3]. Comparison of mRNA from two conditions by competitive hybridization to these probes is used to identify differentially expressed genes [1]. In the case of spotted microarrays, these are performed either with labeled cDNA prepared from separate mRNA preparations co-hybridized to the same array, or as is increasingly the case, by employing genomic DNA (gDNA) as a standard reference [4]. In the latter case, each cDNA preparation is hybridized separately alongside a gDNA reference and differential expression is determined using a ratio of ratios. The use of gDNA corrects for most spatial and spot-dependent biases inherent with microarrays, and also allows direct comparison between ...
In post-genomic cancer research laboratories, microarray-based techniques are commonly employed to find valuable insights into differences in an individuals tumor as compared with constitutional DNA, mRNA (or miRNA) expression and protein activity. The application of these high-throughput technologies is providing huge amounts of data that should be computationally processed and analyzed in order to extract valuable biological information.. The Bioinformatics Unit is currently working with various CNIO wet-lab groups and external collaborators on projects related to the analysis of large-scale data sets (i.e. gene expression and miRNAs microarrays, ChIP on chip, etc.). As a matter of course, we carry out the processing and normalization of several gene expression microarray platforms (Agilent, Affymetrix, Codelink, etc.). Additionally, statistical differential expression testing, geneset-oriented studies and functional analysis of gene lists of interest are offered to both CNIO users and ...
Background: Until recently, few genomic reagents specific for non-human primate research have been available. To address this need, we have constructed a macaque-specific high-density oligonucleotide microarray by using ...
In "single-channel microarrays" or "one-color microarrays", the arrays provide intensity data for each probe or probe set indicating a relative level of hybridization with the labeled target. However, they do not truly indicate abundance levels of a gene but rather relative abundance when compared to other samples or conditions when processed in the same experiment. Each RNA molecule encounters protocol and batch-specific bias during amplification, labeling, and hybridization phases of the experiment making comparisons between genes for the same microarray uninformative. The comparison of two conditions for the same gene requires two separate single-dye hybridizations. Several popular single-channel systems are the Affymetrix "Gene Chip", Illumina "Bead Chip", Agilent single-channel arrays, the Applied Microarrays "CodeLink" arrays, and the Eppendorf "DualChip & Silverquant". One strength of the single-dye system lies in the fact that an aberrant sample cannot affect the raw data derived from ...
Different concentrations of IMP may be correlated with different developmental states at the different time points. Although some researchers have reported that IMP content increases during the growth process [12], our result revealed that the IMP content did not consecutively increase from 2 to 12 wk. This is likely because IMP metabolism was considered merely a part of purine metabolism, meaning IMP was an intermediate compound in purine metabolism. Because ATP and GTP are utilized in energy generation, IMP has an affinity for energy metabolic processes [21]. Thus, the efficiency of the de novo synthesis of IMP, the rate of the compensatory pathway of IMP synthesis and the rate of IMP utilization to synthetize other nucleic acids determines the concentration of IMP [22]. The enzymes investigated here, which were involved in these three processes, interacted with more than one substrate. The genes that had a significant effect on the efficiency of IMP metabolism were those that participated in ...
We have used the recently completed set of all homozygous diploid deletion mutants in budding yeast, S. cerevisiae, to screen for new mutants conferring sensitivity to ionizing radiation. In each strain a different open reading frame (ORF) has been replaced with a cassette containing unique 20-mer sequences that allow the relative abundance of each strain in a pool to be determined by hybridization to a high-density oligonucleotide array. Putative radiation-sensitive mutants were identified as having a reduced abundance in the pool of 4,627 individual deletion strains after irradiation. Of the top 33 strains most sensitive to radiation in this assay, 14 contained genes known to be involved in DNA repair. Eight of the remaining deletion mutants were studied. Only one, which deleted for the ORF YDR014W (which we name RAD61), conferred reproducible radiation sensitivity in both the haploid and diploid deletions and had no problem with spore viability when the haploid was backcrossed to wild-type. ...
Bioconductor version: Development (3.7) Intra-miR-ExploreR, an integrative miRNA target prediction bioinformatics tool, identifies targets combining expression and biophysical interactions of a given microRNA (miR). Using the tool, we have identified targets for 92 intragenic miRs in D. melanogaster, using available microarray expression data, from Affymetrix 1 and Affymetrix2 microarray array platforms, providing a global perspective of intragenic miR targets in Drosophila. Predicted targets are grouped according to biological functions using the DAVID Gene Ontology tool and are ranked based on a biologically relevant scoring system, enabling the user to identify functionally relevant targets for a given miR.. Author: Surajit Bhattacharya and Daniel Cox Maintainer: Surajit Bhattacharya ,sbhattacharya3 at student.gsu.edu, ...
Bioconductor version: Release (3.6) Intra-miR-ExploreR, an integrative miRNA target prediction bioinformatics tool, identifies targets combining expression and biophysical interactions of a given microRNA (miR). Using the tool, we have identified targets for 92 intragenic miRs in D. melanogaster, using available microarray expression data, from Affymetrix 1 and Affymetrix2 microarray array platforms, providing a global perspective of intragenic miR targets in Drosophila. Predicted targets are grouped according to biological functions using the DAVID Gene Ontology tool and are ranked based on a biologically relevant scoring system, enabling the user to identify functionally relevant targets for a given miR.. Author: Surajit Bhattacharya and Daniel Cox Maintainer: Surajit Bhattacharya ,sbhattacharya3 at student.gsu.edu, ...
The DNA Microarray Facility provides access to various forms of technology for gene expression analysis, pairticularly DNA microarray technologies, to members o...
TY - JOUR. T1 - Sustained upregulation of inflammatory chemokine and its receptor in aneurysmal and occlusive atherosclerotic disease. T2 - Results from tissue analysis with cDNA macroarray and real-time reverse transcriptional polymerase chain reaction methods. AU - Yamagishi, Masakazu. AU - Higashikata, Takeo. AU - Ishibashi-Ueda, Hatsue. AU - Sasaki, Hiroaki. AU - Ogino, Hitoshi. AU - Iihara, Koji. AU - Miyamoto, Susumu. AU - Nagaya, Noritoshi. AU - Tomoike, Hitonobu. AU - Sakamoto, Aiji. PY - 2005/12/1. Y1 - 2005/12/1. N2 - Background: Although cytokines are known to be pivotal in the development of atherosclerotic diseases, few data exist regarding their expressions in the established stages such as aneurysmal or occlusive lesions. Therefore, in the present study the gene expression levels of cytokine-related substances in abdominal aortic aneurysm (AAA) and carotid artery stenosis (CAS) were determined using cDNA macroarray and real-time reverse transcriptase polymerase chain reaction ...
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PubMed Central Canada (PMC Canada) donne libre accès en ligne à des archives numériques fiables et permanentes qui contiennent le texte intégral de publications de recherches évaluées par des pairs en santé et en sciences de la vie. Il fait fond sur PubMed Central (PMC), les archives numériques gratuites des National Institutes of Health (NIH) des États-Unis qui proviennent de revues biomédicales et sur les sciences de la vie, et il est membre du réseau élargi PMC International (PMCI).
Serrated adenocarcinoma (SAC) is a recently recognized colorectal cancer (CRC) subtype accounting for 7.5 to 8.7% of CRCs. It has been shown that SAC has a poorer prognosis and has different molecular and immunohistochemical features compared with conventional carcinoma (CC) but, to date, only one previous study has analyzed its mRNA expression profile by microarray. Using a different microarray platform, we have studied the molecular signature of 11 SACs and compared it with that of 15 matched CC with the aim of discerning the functions which characterize SAC biology and validating, at the mRNA and protein level, the most differentially expressed genes which were also tested using a validation set of 70 SACs and 70 CCs to assess their diagnostic and prognostic values. Microarray data showed a higher representation of morphogenesis-, hypoxia-, cytoskeleton- and vesicle transport-related functions and also an overexpression of fascin1 (actin-bundling protein associated with invasion) and the ...
Remove 90% of mammalian RNA from ... Simple procedure takes less than 2 hours ... Works with any bacterial species ... Seamless integration with MICROB Express ... Enables microarray expression analysis with bacteri...,Bacterial,RNA,Isolation,From,Infected,Eukaryotic,Hosts,biological,advanced biology technology,biology laboratory technology,biology device technology,latest biology technology
Given the great publicity of DNA microarrays techniques in recent years, many researchers have put their blind trust into this methodology, only to be overwhelmed by the confusing data generated. Knowing the major differences between differential display and DNA microarrays, both in theory and in practice, may help you to find the genes of real interest and save your valuable resources and effort.. Both differential display (DD) and microarrays are conceptually simple, however, the two methods are principally different. The fundamental difference is that differential display visualizes the mRNAs in subsets directly without any data normalization after their amplification and labeling by either isotopes or fluorescent dyes. In contrast, DNA microarrays visualize the mRNAs indirectly after the hybridization of extremely complex mRNA probes as first-strand cDNAs with fluorescent labels to a set of cDNA templates spotted on a glass surface. In fact, a cDNA probe used for microarray can be so complex ...
A comprehensive pipeline for analyzing and interactively visualizing genomic profiles generated through commercial or custom aCGH arrays. As inputs, rCGH supports Agilent dual-color Feature Extraction files (.txt), from 44 to 400K, Affymetrix SNP6.0 and cytoScanHD probeset.txt, cychp.txt, and cnchp.txt files exported from ChAS or Affymetrix Power Tools. rCGH also supports custom arrays, provided data complies with the expected format. This package takes over all the steps required for individual genomic profiles analysis, from reading files to profiles segmentation and gene annotations. This package also provides several visualization functions (static or interactive) which facilitate individual profiles interpretation. Input files can be in compressed format, e.g. .bz2 or .gz.
Comparative genomic hybridizations have been used to examine genetic relationships between bacteria. The microarrays used in these experiments may have open reading frames from one or more reference strains, or they may be composed of random DNA fragments from a large number of strains (mixed-genome microarrays; MGM). Herein both experimental and virtual arrays are analyzed to assess the validity of genetic inferences from these experiments with a focus on MGMs. Empirical data is analyzed from an Enterococcus MGM while a virtual MGM is constructedin silico using sequenced genomes (Streptococcus). On average a small MGM is capable of correctly deriving phylogenetic relationships between seven species of Enterococcus with 100% (n=100 probes) and 95% (n=46 probes) accuracy; more probes are required for intra-specific differentiation. Compared to multilocus sequence methods and whole-genome microarrays, MGM provides additional discrimination between closely related strains and offers the possibility ...
Affymetrix is dedicated to developing state-of-the-art technology for acquiring, analyzing, and managing complex genetic information for use in biomedical research. Affymetrix sells GeneChip® brand microarrays.
Microarrays are now routinely employed to characterize gene expression of thousands of genes from a single hybridization. The genome wide gene expression profile aids in the understanding of genes that may be regulated in a particular pathological condition. This paper provides an overview of microarray technology and its recent developments followed by its usage in studies of cardiovascular disease and how it pertains to viral and parasitic infections of the heart.
The RNA extracted from human fetal retinas and hybridized to the arrays was of high quality and purity (Table 3). Microarray quality controls were within manufacturer recommendations, and control values were comparable between arrays (Table 3). In addition, on all arrays the average signal values of the poly(A) RNA and hybridization controls increased relative to the order of spike concentrations (lys, phe, thr, dap and bioB, bioC, bioD, cre, respectively) indicating efficient labeling and hybridization of all samples. The full set of microarray data has been deposited with the NCBI Gene Expression Omnibus repository under accession number GSE12621. We generated two lists of differentially expressed genes: macula versus surround; and macula versus nasal. We selected a p-value cut-off of ,0.01 which gave a false discovery rate (step up method) of 14%. Using DAVID, we found the differentially expressed genes were clustered according to their functional roles, or biological process, generating over ...
This unit provides protocols for the amplification and labeling of mRNA (and the necessary controls) for hybridization to oligonucleotide arrays
SAM is a method for identifying genes on a microarray with statistically significant changes in expression, developed in the context of an actual biological experiment. SAM was successful in analyzing this experiment as well as several other experiments with oligonucleotide and cDNA microarrays (data not shown).. In the statistics of multiple testing (28-30), the family-wise error rate (FWER) is the probability of at least one false positive over the collection of tests. The Bonferroni method, the most basic method for bounding the FWER, assumes independence of the different tests. An acceptable FWER could be achieved for our microarray data only if the corresponding threshold was set so high that no genes were identified. The step-down correction method of Westfall and Young (29), adapted for microarrays by Dudoit et al. (http://www.stat.berkeley.edu/users/terry/zarray/Html/matt.html), allows for dependent tests but still remains too stringent, yielding no genes from our data.. Westfall and ...
Shi L, Campbell G, Jones WD, Campagne F, Wen Z, Walker SJ, Su Z, Chu TM, Goodsaid FM, Pusztai L, Shaughnessy JD, Oberthuer A, Thomas RS, Paules RS, Fielden M, Barlogie B, Chen W, Du P, Fischer M, Furlanello C, Gallas BD, Ge X, Megherbi DB, Symmans WF, Wang MD, Zhang J, Bitter H, Brors B, Bushel PR, Bylesjo M, Chen M, Cheng J, Cheng J, Chou J, Davison TS, Delorenzi M, Deng Y, Devanarayan V, Dix DJ, Dopazo J, Dorff KC, Elloumi F, Fan J, Fan S, Fan X, Fang H, Gonzaludo N, Hess KR, Hong H, Huan J, Irizarry RA, Judson R, Juraeva D, Lababidi S, Lambert CG, Li L, Li Y, Li Z, Lin SM, Liu G, Lobenhofer EK, Luo J, Luo W, McCall MN, Nikolsky Y, Pennello GA, Perkins RG, Philip R, Popovici V, Price ND, Qian F, Scherer A, Shi T, Shi W, Sung J, Thierry-Mieg D, Thierry-Mieg J, Thodima V, Trygg J, Vishnuvajjala L, Wang SJ, Wu J, Wu Y, Xie Q, Yousef WA, Zhang L, Zhang X, Zhong S, Zhou Y, Zhu S, Arasappan D, Bao W, Lucas AB, Berthold F, Brennan RJ, Buness A, Catalano JG, Chang C, Chen R, Cheng Y, Cui J, Czika W, ...
DNA microarrays are a potentially disruptive technology in the medical field, but their use in such settings is limited by poor reliability. Microarrays work on the principle of hybridization and can only be as reliable as this process is robust, yet little is known at the molecular level about how the surface affects the hybridization process. This work uses advanced molecular simulation techniques and an experimentally-parameterized coarse-grain model to determine the mechanism by which hybridization occurs on surfaces and to identify key factors that influence the accuracy of DNA microarrays. Comparing behavior in the bulk and on the surface showed, contrary to previous assumptions, that hybridization on surfaces is more energetically favorable than in the bulk. The results also show that hybridization proceeds through a mechanism where the untethered (target) strand often flips orientation. For evenly-lengthed strands, the surface stabilizes hybridization (compared to the bulk system) by reducing
The investigation of global gene expression changes induced by celecoxib by the powerful DNA microarrays technology provided an extensive list of potentially novel targets for celecoxib. A few previously reported genes affected by celecoxib and involved in the regulation of cell cycle and apoptosis, such as BAX, SKP2, BCL2L1, CDK2, CDKN1A, and TP53, were among the celecoxib-modulated and PCR-validated genes in our study (Table 1). However, most of the validated genes in Table 1 have not been reported previously in the vast body of celecoxib literature to be the potential targets of celecoxib. Examples of these novel celecoxib-modulated genes identified in our study include genes such as protein kinases, ATM and mTOR/FRAP, that are centrally involved in cell survival, growth, and metabolism (22, 23). ATM is a critical signaling molecule and plays a crucial role in numerous DNA damage response pathways in cells (Supplementary Fig. S4; refs. 22, 24), and mTOR occupies a central position in a ...
[110 Pages Report] Check for Discount on 2017-2022 Global and Japan DNA and Gene Chip Market Analysis Report report by QYResearch Group. The global DNA and Gene Chip market is valued at...
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0279]There may be applications where it is desired to isolate and analyze only some selected strands from a complex strand mixture. There are 50,000 to 100,000 genes in the human genome, that together account for several percent of the genomic DNA, and that would be of primary interest for clinical diagnostics. Thus, it may be desirable that only 100,000 or so fragments be isolated and analyzed, instead of millions of restriction fragments from the patients entire genome. Instead of preparing an array that includes all possible variable oligonucleotide segments of a certain length, a binary sorting array can be prepared that contains selected oligonucleotides whose variable segments are chosen so that they match the termini of every fragment of interest, and only the termini of those fragments, i.e. the segments are long enough to isolate only the fragment of interest. Once the first human genome is sequenced and all the genes are identified, and consequently all the accessible restriction ...
Breakpoint characterization by 44K oligonucleotide array-CGH. a: 7.1 Mb deletion at 8p [arr 8p23.3p23.1(191,530-7,303,237)x1] and b: 30 Mb duplication at 15q
A white-box approach to microarray probe response characterization: the BaFL pipeline. . Biblioteca virtual para leer y descargar libros, documentos, trabajos y tesis universitarias en PDF. Material universiario, documentación y tareas realizadas por universitarios en nuestra biblioteca. Para descargar gratis y para leer online.
Hi Nainhua, as Tine pointed out I would suggest you choose multiple.... or you do it the hard way. For our purposes (MapMan visualization based on classification) I test, if the multiple genes hit by one probeset, have a similar function. If this is the case I mix the annotations assuming that it might be a [diverged] gene family, in which case there might be some information left (Affy used to tag them _s_, but affy is way outdated) when I sample the whole class. However, if a probesets turns out to hit genes of different classes [non gene families ancient _x_ tag] (e.g. glycolysis and say proteasom dependent degradation) I annotate the probeset as hitting multi and put it in a special non-evaluate able class. You could also try to determine if it is really a gene family that is hit, in which case the annotations would be similar as well anyway. But that is a lot of querying and eventually needs manual interaction. Thanks for your work. Cheers, Björn Nianhua Li wrote: , Hi, Tine, Bjorn, ...
The clinical utility of microarray technologies when used in the context of prenatal diagnosis lies in the technologys ability to detect submicroscopic copy number changes that are associated with clinically significant outcomes. We have carried out