Sentence examples for microarray datasets use from inspiring English sources

One common example is that microarray datasets use gene probe IDs but metabolic pathways use gene locus names.

Because microarray datasets use different platforms and the data are presented in different formats, the microarray data were adjusted to similar scale and distribution patterns before class prediction based on four guidelines (for detail, see Additional file 2).

Microarray datasets used in this paper were either generated by us as previously described (Chen-Plotkin et al. 2008), downloaded from GEO (http://www.ncbi.nlm.nih.gov/geo/index.cgi), or obtained from the authors directly.

We performed experiments on 12 highly imbalanced microarray datasets using linear and Gaussian kernel, achieving the highest average predictive performance with our approach compared with the most well-known feature selection strategies.

The purpose of this study was to extract and evaluate such seasonal gene expression characteristics from the existing multiple microarray datasets using the goldfish model.

Note that all the microarray datasets used are normalized using RMA, which has been reported to be more accurately reflective of biological changes compared to other methods like MAS5 (Affymetrix).

Six additional microarray datasets using cDNA, oligo, or Affymetrix arrays are available through Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/sites/entrez?db=geo) and citations for publications are also linked to these public data sets [33], [35], [36].

Additional file 3: Summary of the microarray datasets used in the study.

Microarray datasets used for gene signature generation: distribution of patients according to clinical variables.

Clinical validation was performed in publicly available microarray datasets using disease free and overall survival endpoints.

A molecular classifier was created based on a combined analysis of two microarray datasets (using 66 thyroid samples).