Sentence examples for microarray problems associated from inspiring English sources

This was actually useful when we took the ratio of the signal for each gene relative to that for reference RNA, thus circumventing the microarray problems associated with spot-to-spot variation and hybridization variation for different nucleotide sequences.

Only about 90 common genes (out of hundreds) were identified to cycle diurnally in the liver in two separate microarray experiments (Delaunay & Laudet, 2002), pointing to problems associated with microarray reproducibility.

Special quality control criteria for array processing and analysis need to be used to overcome previous problems associated with microarray technologies.

However, owing to the large number of genes and to the small number of samples, there are many statistical problems associated with microarray data [9], [10], which makes the detection of differential gene expression a challenging task.

Furthermore, a supervised, pathway-based analysis reduces multiple testing problems associated with microarray analysis by focusing on a limited number of pathways instead of analyzing all of the probes available on the microarray.

Furthermore, by leaving probes that are not relevant to the biological processes of interest out of the analysis, statistical noise and multiple testing problems associated with microarray analysis are reduced.

As RNA-seq is based on counting sequences, cross hybridisation problems associated with microarrays are avoided b).

Introduction of controlled changes into the expression dataset enables us to address many problems associated with pre-processing and analysis of microarray data, including the quality dependence of the analysis from the threshold of minimal gene expression, the influence of fold change restrictions, and other factors.

Microarray technology offers great potential for unravelling some of the problems associated with breast cancer.

The restriction on the number of genes we analyzed, given a modest number of samples, circumvents methodological problems associated with other large scale expression studies such as microarray analysis that often preclude proper statistical analysis due to a high false discovery rate and huge family-wise errors.

Problems associated with sensitivity and reproducibility have been reported for microarray analyses, even for the ones conducted with manufactured Affymetrix Gene Chips [ 22].