Sentence examples for microarray analysis methodologies from inspiring English sources

Another technical challenge for microarray analysis methodologies comes from the order of discretized gene expression values.

However, the significantly differentially expressed genes were defined from the convergence of the three microarray analysis methodologies.

As the three microarray analysis methodologies produced unrelated measures of signal intensity, only MAS5.0 signal data were used to define the gene expression clusters.

Even when the number of classes is equal to 2, the new method is completely different with other microarray analysis methodologies.

When this genes are ranked by current microarray analysis methodologies, for example by calculating the Gini index of gene A using dataset D g i n i A (D ) = ∑ i = 1 m R i d ⋅ g i n i R i where d = | D|, the two genes would have the same rank.

Our study included analysis of scrapie strain 22L which has not previously been reported in gene expression profiling studies, and implemented refined microarray analysis methodologies that allowed for identification of significant disease-associated alterations in gene expression using minimal numbers of mice.

Using the optimized experimental protocol complemented with the microarray analysis methodology, as presented in this study, we identify 49 genes as DE between the MNs and dCINs.

Using this optimized experimental protocol in combination with our microarray analysis methodology we find 49 differentially expressed genes between the motor neurons and the interneurons that reflect the functional differences between these two cell populations in generating and transmitting the motor output in the rodent spinal cord.

All differentially expressed Affymetrix probe set identifiers, along with their associated fold change and p-value, were generated using standard microarray analysis methodology (See Methods) and accessed via tab-delimitated format (all datasets available as Additional File 3).

AP has performed microarray data analysis, methodology development, programming and pathway analysis.

Microarray analysis is a powerful methodology for high throughput gene expression study which contributes to the understanding of complex events or biological systems [ 35].