oligonucleotide microarray platforms cytochip oligo 8 × 60 k  (BlueGnome Limited)

Journal: Heliyon

Article Title: Automated high-throughput DNA synthesis and assembly

doi: 10.1016/j.heliyon.2024.e26967

Figure Lengend Snippet: Typical oligonucleotide synthesizers. A, Column-based oligonucleotide synthesizers. B, High-throughput microarray-based oligonucleotide synthesizers. C, Enzymatic oligonucleotide synthesizers.

Article Snippet: Furthermore, in 2007, CombiMatrix's oligonucleotide microarray platform contained 12,544 individually addressable microelectrodes in a semiconductor matrix.

Techniques: High Throughput Screening Assay, Microarray

Journal: Heliyon

Article Title: Automated high-throughput DNA synthesis and assembly

doi: 10.1016/j.heliyon.2024.e26967

Figure Lengend Snippet: Schematic representations of assembly methods for DNA synthesis. A, Polymerase cycling assembly (PCA). B, Ligase chain reaction (LCR). C, D, Different strategies for dealing with microarray oligonucleotide complexities.

Article Snippet: Furthermore, in 2007, CombiMatrix's oligonucleotide microarray platform contained 12,544 individually addressable microelectrodes in a semiconductor matrix.

Techniques: DNA Synthesis, Polymerase Cycling Assembly, Microarray

Journal: PLoS ONE

Article Title: MicroRNA Expression Profiles of Whole Blood in Lung Adenocarcinoma

doi: 10.1371/journal.pone.0046045

Figure Lengend Snippet: The scatter-plots show RT-PCR quantification cycle (C q ) values and log 2 -transformed microarray signal values for microRNAs let-7e , miR-22 , miR-30a-5p , miR-185 , miR-210 , and miR-423-5p (n = 11). Pearson correlation coefficients (r) and their 95% confidence intervals and associated P values, and best fitting (least squares) lines are also shown.

Article Snippet: A two-color, oligonucleotide microarray platform from Exiqon® was used to quantify levels of 1282 human microRNAs and 23 human non-microRNAs of <200 nucleotides in the RNA isolated from whole blood specimens.

Techniques: Reverse Transcription Polymerase Chain Reaction, Transformation Assay, Microarray

Journal: PLoS ONE

Article Title: MicroRNA Expression Profiles of Whole Blood in Lung Adenocarcinoma

doi: 10.1371/journal.pone.0046045

Figure Lengend Snippet: A . Unsupervised clustering of the 45 samples of this study by log 2 -transformed microarray signal values of all 395 expressed microRNAs. The numbers indicate identities of the 45 subjects, with cases (n = 22) and controls (n = 23) shown in black and grey, respectively. The sample tree with optimized leaf-ordering is drawn using Pearson correlation for distance metric and average linkage for cluster-to-cluster distance, and the scale for it represents node-heights. B . Supervised clustering of microRNAs by their log 2 -transformed microarray signal values. The heat-map, with the pseudo-color scale underneath, shows log 2 -transformed microarray signal values of the 43 microRNAs whose expression is altered >25% in either direction in the cases compared to the controls. The gene tree is drawn as in A .

Article Snippet: A two-color, oligonucleotide microarray platform from Exiqon® was used to quantify levels of 1282 human microRNAs and 23 human non-microRNAs of <200 nucleotides in the RNA isolated from whole blood specimens.

Techniques: Transformation Assay, Microarray, Expressing

Journal: PLoS ONE

Article Title: MicroRNA Expression Profiles of Whole Blood in Lung Adenocarcinoma

doi: 10.1371/journal.pone.0046045

Figure Lengend Snippet: Dot-plots with medians and inter-quartile ranges of log 2 -transformed microarray signal values for the 22 cases ( black ) and 23 controls ( grey ) are shown for the four microRNAs that are present in a majority of the classifiers generated in internal cross-validation analyses using the linear support vector machines and top-scoring pairs classification methods.

Article Snippet: A two-color, oligonucleotide microarray platform from Exiqon® was used to quantify levels of 1282 human microRNAs and 23 human non-microRNAs of <200 nucleotides in the RNA isolated from whole blood specimens.

Techniques: Transformation Assay, Microarray, Generated, Plasmid Preparation

Journal: PLoS ONE

Article Title: MicroRNA Expression Profiles of Whole Blood in Lung Adenocarcinoma

doi: 10.1371/journal.pone.0046045

Figure Lengend Snippet: A . Receiver operating characteristic curves, the areas under curve ( AUC ) for age, and the line of identity, x = y , with an AUC of 0.5, are shown. B . Correlation with microRNA expression. Values for the clinical variables were correlated with microarray signal values for the 395 expressed microRNAs (n = 45 for age; n = 39 for others). The curves depict frequency histograms of Pearson correlation coefficients ( r ) with a bin of 0.025. Curves were smoothened using four neighbors for averaging and a zero order polynomial. Correlations are also shown for the random variable resampled WBC count for which values were generated by resampling the WBC count data.

Article Snippet: A two-color, oligonucleotide microarray platform from Exiqon® was used to quantify levels of 1282 human microRNAs and 23 human non-microRNAs of <200 nucleotides in the RNA isolated from whole blood specimens.

Techniques: Expressing, Microarray, Generated

Journal: BMC Genomics

Article Title: Multiple platform assessment of the EGF dependent transcriptome by microarray and deep tag sequencing analysis

doi: 10.1186/1471-2164-12-326

Figure Lengend Snippet: Microarray interplatform analysis . (A) Overlap of unique and named genes shared among the 3 microarray platforms used in this study. The pool of 17070 shared genes was used for further cross-platform analysis. The total numbers of genes for each platform and for all platforms combined are indicated. (B) Overlap of significantly regulated genes at 6 h after EGF treatment considering each of the 3 microarray platforms independently.

Article Snippet: Here we use a combined approach to study the EGF dependent transcriptome of HeLa cells by using multiple long oligonucleotide based microarray platforms (from Agilent, Operon, and Illumina) in combination with digital gene expression profiling (DGE) with the Illumina Genome Analyzer.

Techniques: Microarray

Journal: BMC Genomics

Article Title: Multiple platform assessment of the EGF dependent transcriptome by microarray and deep tag sequencing analysis

doi: 10.1186/1471-2164-12-326

Figure Lengend Snippet: GSEA analysis on significantly regulated gene sets across microarray platforms . Profile of the Running ES Score & Positions of Gene Set Members on the Rank Ordered List using 6 h EGF treatment data according to each of the three microarray platforms. In each panel, the vertical black lines indicate the position of each of the genes of the tested gene set in the reference data set (ranked by average of the three respective EGF versus control log2ratios of replicate experiments). The green curve plots the ES (enrichment score), which is the running sum of the weighted enrichment score obtained from GSEA software. Within each queried gene set, the farther the position of a gene to the left (red) implies a higher correlation with EGF up-regulated genes in the reference platform, and the farther to the right (blue) implies a higher correlation with genes down-regulated upon EGF treatment in the reference platform. Studied gene sets correspond to lists of up- or down-regulated genes in each platform at 6 h of EGF treatment. Significantly enriched data sets are defined according to GSEA default settings (p < 0.001 and a false discovery rate (FDR) < 0.25). R.L.M = ranked list metric.

Article Snippet: Here we use a combined approach to study the EGF dependent transcriptome of HeLa cells by using multiple long oligonucleotide based microarray platforms (from Agilent, Operon, and Illumina) in combination with digital gene expression profiling (DGE) with the Illumina Genome Analyzer.

Techniques: Microarray, Software

Journal: BMC Genomics

Article Title: Multiple platform assessment of the EGF dependent transcriptome by microarray and deep tag sequencing analysis

doi: 10.1186/1471-2164-12-326

Figure Lengend Snippet: Microarray versus DGE analysis . (A) Overlap of unique and named genes shared among the 3 microarray platforms and genes detected by DGE. The pool of 14645 shared genes was used for further cross-platform analysis. The total numbers of genes for each platform and for all platforms combined are indicated. (B) Overlap of significantly regulated genes considering the 3 microarray platforms at 6 h after EGF treatment and the genes found regulated after assessing significance by grouping microarray and DGE data in a RankProd analysis. Left panels show up-regulated genes and right panels show down-regulated genes.

Article Snippet: Here we use a combined approach to study the EGF dependent transcriptome of HeLa cells by using multiple long oligonucleotide based microarray platforms (from Agilent, Operon, and Illumina) in combination with digital gene expression profiling (DGE) with the Illumina Genome Analyzer.

Techniques: Microarray

Journal: BMC Genomics

Article Title: Multiple platform assessment of the EGF dependent transcriptome by microarray and deep tag sequencing analysis

doi: 10.1186/1471-2164-12-326

Figure Lengend Snippet: Correlation between microarrays and Illumina GA-I sequencing . (A) Comparison of estimated log2ratios from DGE ( Y -axis) and the mean of all microarray platforms ( X -axis). We consider only genes that were interrogated using all platforms and genes with a mean number of counts across lanes greater than 0. Genes with counts greater than 32 reads (colored red or green) or less than (black) 32 reads in at least one sample are shown. (Red dots) Genes called differentially expressed based on DGE data at an 10% FDR by RankProd. (Green dots) Genes not called as differentially expressed but above 32 counts. (Inset box) Correlation between technologies is higher when considering genes above the 32 count detection level (0.57) than when all genes are included (0.49). (B-C) Concordance at the top (CAT) plots of the different platforms with the 500 top genes from a reference platform, shown for Agilent in (B) and DGE in (C). See inset box for color codes identifying each platforms compared to the remaining platform used as reference. (D) Correlation plots with regression lines between log2ratios of the five high content platforms measurements (Y-axis) and quantitative real time PCR results using SYBR green assays (X-axis), based on measurements for 21 genes at the 6 h time point (see Additional file , Table S1).

Article Snippet: Here we use a combined approach to study the EGF dependent transcriptome of HeLa cells by using multiple long oligonucleotide based microarray platforms (from Agilent, Operon, and Illumina) in combination with digital gene expression profiling (DGE) with the Illumina Genome Analyzer.

Techniques: Sequencing, Microarray, Real-time Polymerase Chain Reaction, SYBR Green Assay

Journal: BMC Genomics

Article Title: Multiple platform assessment of the EGF dependent transcriptome by microarray and deep tag sequencing analysis

doi: 10.1186/1471-2164-12-326

Figure Lengend Snippet: Top regulated genes derived from meta-analysis . RankProd analysis of the combination of microarray and Illumina GA-I ultrasequencing data sets. Heatmap of the top 50 up and down-regulated genes detected in all four platforms ordered by Median Fold Change (all have RankProd adjusted p-values < 0.0001). IL11, IL8, PLAUR, ANXA10 and FOS were validated by RT-qPCR showing concordant results (See Additional file , Table S1). The full RankProd matrix from these experiments is accessible in Additional file , Table S5. The list of all 1164 significantly regulated genes (median |FC| > 1.2 and RankProd q-value < 0.05) is given in Additional file , Table S6.

Article Snippet: Here we use a combined approach to study the EGF dependent transcriptome of HeLa cells by using multiple long oligonucleotide based microarray platforms (from Agilent, Operon, and Illumina) in combination with digital gene expression profiling (DGE) with the Illumina Genome Analyzer.

Techniques: Derivative Assay, Microarray, Quantitative RT-PCR