Sentence examples for microarray dataset for from inspiring English sources
Microarray dataset for Dam mutant was obtained from Robbins-Manke et al [3].
Therefore, we examined our microarray dataset for genes with expression levels correlated either strongly positively (≥0.8) or inversely (≤−0.8) with ABCB7 gene expression levels.
Finally, we used a microarray dataset for yeast Saccharomyces cerevisiae that demonstrated the scalability and precision of QAPgrid and its possibility as a novel tool for functional genomics.
The Affymetrix microarray dataset for the samples are deposited with Gene Expression Omnibus (GEO) with accession numbers, GSE18349, GSM458064, and GSM458065.
Since downregulation of Schwann cell miRNAs might also control important steps of proper myelination, we analyzed the microarray dataset for those miRNAs that were significantly downregulated upon myelination and significantly reduced by ablation of Dicer from Schwann cells (either at E17 or at p4).
One of the first works on the analysis of a gene expression microarray dataset for yeast was presented by Eisen et al. [43], which is among the most cited works in microarray of the Saccharomyces cerevisiae (a highly cited contribution as reported by Google Scholar and ISI Web of knowledge figures of 10,054 and 6,963, respectively).
We attained curated microarray datasets for cervical cancer, acute myeloid leukemia and breast cancer (letrozole treated) [13] [15].
The full microarray datasets for the Crx-/ and Crx-/- Nrl-/- analyses are given in Tables S5 and S6.
ImmGen is a public data gene-expression repository consisting of whole-genome microarray datasets for nearly all characterized cell populations of the adaptive and innate immune systems [20].
In order to find control genes for comparing human-chimpanzee gene expression across multiple tissues, we developed a pipeline that draws on information from published microarray datasets for identifying candidate normalizers.
Normalisation was carried out by Robust Multichip Analysis (RMA) and differentially expressed contigs were identified across the normalised microarray datasets for biological replicates using linear modelling in limma in R v2.7.1 (Linear Models for Microarray Data) [57].
