Sentence examples for microarray platforms remains from inspiring English sources

So far, analyzing gene expression across different microarray platforms remains a challenge.

This is inspired by the FDA-led Microarray Quality Control (MAQC) Consortium project [ 5], where one of its findings is that while noise is inevitable in microarray experiments, the rank correlation between different experimental groups and microarray platforms remains high.

Combining raw data from microarray studies on different platforms remains problematic due to data that are not commensurable.

Although numerous investigations have compared gene expression microarray platforms, preprocessing methods and batch correction algorithms using constructed spike-in or dilution datasets, there remains a paucity of studies examining the properties of microarray data using diverse biological samples.

There are two major microarray platforms that have been widely used: cDNA microarrays and oligonucleotide microarrays.

Tan, P. K. et al. Evaluation of gene expression measurements from commercial microarray platforms.

Tan, P.K. et al. Evaluation of gene expression measurements from commercial microarray platforms.

Hester, S.D. et al. Comparison of comparative genomic hybridization technologies across microarray platforms.

The US Food and Drug Administration (FDA -led community-wide Microarray Quality Control (MAQC) study generates a large amount oFDA -ledrray data with implementation of ERCs across several commercial microarray platforMicroarray

Because we used two different microarray platforms to study mouse and human HCC, we selected orthologous genes that were present in both microarrays by using curated mammalian orthology from The Jackson Laboratory.

The technical reproducibility of microarray platforms is well established.