Sentence examples for microarray data very from inspiring English sources

The ability to provide thousands of gene expression values simultaneously makes microarray data very useful for phenotype classification.

This makes circadian rhythmic analysis of temporal microarray data very challenging.

The number of genes (features) considered in the analysis of microarray data is very critical.

As discussed above microarray data is very powerful in illustrating cytoarchitectural differences between cases and controls such as dopaminergic neuron loss.

Analysis of the microarray data showed very little changes in the expression of other nuclear receptors in response to the intervention with the exception of CAR, which was upregulated, and RXRα and AhR, which were downregulated, although not necessarily in all treatments.

Microarray data are very noisy and prone to systematic errors [ 34- 39].

Nonetheless, such methods are considered to be strict since the families of microarray data contain very large numbers of genes.

The distribution of the d/a plots from 70-mer oligonucleotide microarray data are very similar to the plots generated from the Affymetrix data.

We estimated the transcriptional regulation structure of A. fumigatus under heat shock conditions using time series microarray data with very short length of time point, i.e., 6.

Hmox1 is early induced at 3 h followed by almost constant expression in the remaining time points whereas RT-PCR and microarray data correlate very well.

Although identification of antisense RNAs which suppress sense transcripts based solely on microarray data is very difficult, we extracted 49 sense-AFAS probes showing such altered expression balances (Table 1).