Sentence examples for microarray datasets and from inspiring English sources

We apply our techniques to publicly available microarray datasets and compare our results with findings discussed in [36].

Here we describe the Rice Oligonucleotide Array Database (ROAD,http://www.ricearray.org), which integrates the most comprehensive public microarray datasets and provides several functional analysis tools.

We chose these treatments based on publicly available microarray datasets, and on the chaperone related functions of CRTs [12].

Mining of public DNA microarray datasets and a quantitative PCR study establish that SULF1 transcripts are upregulated in human pancreatic cancer (Table 1).

MIRNA genes are transcribed by RNAPol II [7], [8], [116] and therefore polyadenylated MIRNA precursor gene transcripts should be detected in the whole genome tiling microarray datasets and evidence (Figure 2) supports this model.

The observed discrepancy between individual tissues and all tissues in table 3 reflects both a bias produced by the way we selected candidate genes from microarray datasets and the difficulty of finding "universal" control genes.

First, experimental samples were analyzed and conclusions were formulated; and second, experimental sets were combined with publicly available microarray datasets and were further analyzed in search of common DE genes.

We applied our method to five human brain microarray datasets and found that global gene expression can be used to predict the chronological age of a normal brain sample.

SPD may be best viewed as a novel tool for synthesizing biological hypotheses because it provides a likely biological progression underlying a microarray dataset and, perhaps more importantly, the candidate genes that regulate that progression.

They used GO category and MeSH term to analyze the microarray dataset and discovered that those changed genes were related with cell death, apoptosis, oxidative stress, inflammation, and neurotransmitters in the brain.

In the data collection and preprocessing step, gene expression clusters were identified from a microarray dataset and cluster expression levels were converted to discrete values.