Sentence examples for microarray data include from inspiring English sources

The microarray data include many genes that are represented by multiple probe-sets.

The lymphoma microarray data include gene expressions of diffuse large B-cell lymphoma, a subtype of non-Hodgkin's lymphoma [ 1].

In addition to genes involved in neurotransmitter packaging and release, the microarray data include transcripts for receptors to a remarkably wide variety of signaling molecules.

Some commonly used methods for analyzing gene co-expression pattern in microarray data include hierarchical clustering [ 11], K-means clustering [ 12], and self organizing maps [ 13].

Two widely used approaches to analyze DNA microarray data include hierarchial clustering of genes with similar expression patterns [ 18] and grouping of biologically related genes into processes or pathways [ 19, 20].

Other putative meiotic transcripts identified within the microarray data include candidates for recombination, such as radiation sensitive RAD51B and RAD51C, disrupted meiotic cDNA (DMC1) and the rice replication protein A1 (RPA).

We describe in detail the methodology applied for analyzing the microarray data including differential expression as well as functional annotation of the identified symbiont genes.

Microarray data (including raw and processed data) have been deposited in National Center for Biotechnology Information's (NCBI's) Gene Expression Omnibus (NCBIGEO GSE7828).

The microarray data included those in the second model as well as those generated from experiment E4.

Using immunoprecipitation, immunohistochemistry and qPCR methods, we validate the microarray data, including altered GABAergic receptor expression in mice lacking the α9 subunit.

We assembled a large collection of microarray data, including tissue surveys, genetic mapping studies, small-molecular perturbation of cell lines, and comparisons of diseased and normal tissues, generated using several microarray platforms (Table 1; Table S1).