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Global transcriptional changes detected using microarrays has improved our knowledge about virus-host interactions [ 17- 19].
Finally, the general quality of printing of both cDNA and oligonucleotide microarrays has improved significantly over the past 5 years.
Analysis of global transcriptional changes using microarrays has improved our knowledge about virus-host interactions as well as mechanisms by which vaccines induce protection.
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Advances in genomics technologies including high-throughput sequencing and DNA microarrays have improved our ability to make genotype phenotype correlations.
CNV prediction algorithms for data derived from SNP microarrays have improved considerably over the last few years, but many predicted segments are still false positives (Winchester et al., 2009) and can only be excluded through visual inspection in analogy to the mandatory inspection of genotyping assay scatterplots derived from SNP-based genome-wide association studies (GWAS WTCCCC, 2007).
The quality of gene expression microarray data has improved dramatically since the first arrays were introduced in the late 1990s.
As we have learned more about the design, chemistry and kinetics of array assays, the quality of microarray data has improved dramatically.
Annotation of microarray platforms has improved greatly over the past several years, but errors in annotation will continue to affect analyses until genomes are completely validated and curated.
In recent years, in silico promoter analysis of differentially expressed genes from microarray data has improved our understanding of the transcriptional regulation of gene expression markedly.
Gene expression profiling using microarray technologies has improved our understanding of breast cancer biology and has led to the development of a breast cancer molecular taxonomy and of multigene 'signatures' to predict outcome and response to systemic therapies.
It is noteworthy that the performance of microarray technology has improved considerably over the years and in addition owes much to the development of better data analysis algorithms (Huber et al., 2002; Wu and Irizarry, 2005).
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