Sentence examples for microarray characteristics and from inspiring English sources

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Microarray characteristics and data have been deposited in the NIH Gene Expression Omnibus (Series accession number: ) according to minimum information about a microarray experiment (MIAME) (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi acc=GSE11264) (Jézéquel et al, 2008).

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In the microarray application, the nonlinear characteristics and small sample sizes always cause high FPR and low SP when detecting the DEGs with current popular methods.

Measurements of fiber characteristics and microarray analysis of the Li 1 mutant and its WT were conducted at 3, 12, and 16 DPA with the goal of enhancing our understanding of cotton fiber elongation.

In this study, we identified a new IFN-γ-producing innate B cell subset (CD11ahiFcγRIIIhi) and showed the phenotypic and morphological characteristics and microarray results of these pathogen-induced B cells.

The histological characteristics and DNA microarray gene expression profiles of the adrenal tumors of these transgenic mice are similar to those of human adrenal NB [ 12, 13].

Immunohistochemical staining of EGFR, pEGFR, EGFRvIII, Her-2/neu, PTEN (phosphatase and tensin homologue deleted on chromosome 10), total and phosphorylated AKT (pAKT) and phosphorylated ERK (pERK) was performed in 232 primary tumours using the tissue microarray platform and related to clinicopathological characteristics and survival.

Tissue microarrays were scored by two pathologists blinded to the clinicopathological characteristics and outcomes of each patient.

DNA microarray analysis of gene expression has identified five subtypes with different gene expression characteristics and differences in behaviour [ 15].

Different RNA quality measures, such as the 28S/18S ratio, the RNA integrity number (RIN) or a degradometer-score have been developed, verified (see [ 43] and references cited therein for an overview) and related to different microarray hybridization characteristics [ 36, 39, 42].

The model is based on a common statistical characteristic of microarray data, and each set of chip data is normalized on the basis of a linear relationship with this model.

The imperfect classification offered by the classifier can be attributed at least in part to experimentally controllable factors such as the differences in sample collection and processing protocols, microarray platform, and patient clinical characteristics.

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