Sentence examples for microarray data limiting from inspiring English sources

Gardner et al. proposed a methodology to construct the gene-gene control network structure for small networks using microarray data, limiting the number of interactions per gene [ 7].

When we re-analyzed the microarray data limiting our analysis to the 96 bHLH proteins listed in the PFAM database, we identified the genes ASCL2 and MYC as differentially regulated in DLD1, SW480, and LS174T cells (see Additional file 3, tab "DLD1_SW480_LS174T_only"). In DLD1 and SW480 cells, the genes ID1, and ITF2 (TCF4) were also differentially regulated.

Recently, the genome-wide microarray data in whole tissue pterygium[ 16] as well as microarray data limited to cultured pterygial fibroblasts,[ 17] have been published.

Currently, the EPA's official dictum on the regulatory use of microarray data is limited to a four-page "Interim Policy on Genomics" issued in June 2002.

For 3 genes (PKP1, DBNL and LYPA3, Table 1) the consistency between real-time PCR and microarray data was limited to 2 of the 3 experimental groups.

Although microarray data is limited from soybean and most plants other than Arabidopsis, the construction of the 27,513 member low redundancy 'unigene' cDNAs for soybean reported in this paper will greatly stimulate this area.

RARα is also significantly over-expressed in the T1 group, if the analysis of the microarray data is limited to the 22 Luminal cell lines and the trend is confirmed by RNA-seq, although the results do not reach statistical significance.

With microarray data, this limit was promptly reached, for example, when a few dozen human samples were analysed.

The clinical application of microarray data is been limited due to requirement to access detailed patient records.

The use of qRT-PCR for cross-validation of microarray data is generally limited to the most significant differentially expressed genes.

The use of microarray technology to explore the molecular signals that underlie these dose-dependent processes has become increasingly common; however, the number of software tools for quantitatively analyzing and interpreting dose-response microarray data has been limited.