Sentence examples for microarray dataset see from inspiring English sources

The remaining 18 genes were common between the real-time RT-PCR dataset and the microarray dataset (see Table 3) and were used to validate our microarray dataset.

The reason for the identical mean R when these two genomes are randomized is probably either that the housekeeping genes show common patterns of expression in different genomes, dominating the mean R value, or alternatively, that there is a constant bias or weak autocorrection between all genes in each microarray dataset (see Additional file 1 for detailed discussion and also [ 11]).

To achieve this, we modified the REACTIN algorithm to calculate a regulatory score of a TF for each samples in a microarray dataset (see "Methods" for details), resulting in an activity profile for each TF binding profile in our ChIP-seq data collection.

We studied the relationship between host and target genes in three different mouse developmental microarray datasets (see methods): embryonic stem cell development (SCD) [ 27], somitogenesis (SG) [ 28] and neurite outgrowth (NO) [ 29].

Differences in the expression profiles of AtPHT1 genes that could lead to differences in function are apparent in a spatiotemporal gene expression map of the Arabidopsis root [ 35], where the resolution of the original microarray-based map has been substantially increased by additional microarray datasets (see Brady et al. [ 36] and references therein).

There were 93 out of 116 NPM1-associated genes found in the CML microarray dataset GSE5550 (see Table  S1 in Supplementary Material available online at http://dx.doi.org/10.1155/2015/610595).org/10.1155/2015/610595

This approach contrasts with what might be called battery gene set testing, in which a large database of gene sets is evaluated on a microarray dataset, to see whether any sets stand out from the others (Dørum et al., 2009; Efron and Tibshirani, 2007; Saxena et al., 2006).

On the other hand, we used a part of publicly available microarray data (GSE9891) as an external independent dataset (See Materials and Methods) [20].

In order to get an insight into the global structure of the complex dataset of this microarray investigation, we performed a principal component analysis (PCA) on a reduced dataset (see Methods) using the steady-state mRNA levels determined by the application of a common reference hybridization strategy (see Methods).

Microarray analysis revealed high selectivity for amino-acid sequence and combinatorial PTM states with reader domains (for complete dataset, see Additional file 3).

Thirteen microarray gene expression datasets (see Table 1) were used as a training dataset to extract the prognostic gene signature, and the two microarray gene expression datasets, Desmedt dataset (GSE7390) [ 22] and the Vijver dataset [ 3], were used as a testing dataset for evaluating the performance of the algorithm.