Sentence examples for microarray studies often from inspiring English sources

The high cost of microarrays plus the complex logistical issues associated with microarray studies, often require that compromises must be made in the number of samples analyzed.

However, microarray studies often generate gene signatures consisting of hundreds of genes, making it difficult to distinguish which gene expression features are critical.

Microarray studies often entail experimental validation which generally is labor-intensive and, thus, only a certain number of genes can be further investigated.

The functional enrichment analyses for the predicted target genes for each miRNA cluster from the miRNA microarray study often showed enrichment for " cancer" related themes, which is likely indirectly reflecting proliferative potential, and also enrichment for the related terms transcription factor regulation and proliferative activity.

Since hundreds or thousands of samples may be needed for population studies, samples for high-throughput microarray studies must often be processed at different times and/or sites.

In fact, microarray studies are often criticized for a lack of rigorous validation due to small sample sizes [ 17, 18].

In the case of microarray studies, that often focus on the identification of differentially expressed genes or the construction of outcome prediction rules, this means that almost all studies report at least a few significant differentially expressed genes or a small prediction error, respectively.

The use of pooled DNA as control for CGH array experiments is novel and in contrast to current practice in bacterial CGH microarray studies where often only one genome is represented in the control channel, despite the array representing several bacterial genomes.

For instance, the early microarray studies involved often only very few replicate samples and they determined differential expression using simplistic statistics, such as fold-change, while it soon became evident that it is essential to consider also the variability over replicate samples.

Microarray-related studies often involve a very large number of genes and small sample size.

Microarray-based studies often involve a very large number of genes and a relatively small sample size.