Sentence examples for microarray data only from inspiring English sources

A particular concern, with gene expression microarray data only getting larger, is developing and testing probe selection techniques.

Averaging the predictions of these classifiers performed best and was significantly better than the model based on microarray data only.

For the majority of these data sets, three secondary data sources increased performance with respect to the baseline model based on microarray data only, being KEGG, OPHID and microRNA.org.

Due to the low observations for microarray data, only a small number of influential genes can reliably be identified [ 20].

Of the thousands of genes in a microarray data, only a small fraction are informative from the aspect of biological meaning or classification performance [ 13].

Although both the EPA and the FDA have discussed possible uses of microarray data, only the FDA has issued requirements for the submission of such data.

In this manuscript, we consider not only microarray data but also high-throughput data from multiple biological levels.

A tendency towards lower expression levels in SCARKO testes was also noted for Cdh2 (Figure 5D), Espn (Figure 5E) and Jam3 (Figure 5I) from day 10 on (confirming the microarray data) but significant differences were only found from day 15 on (Espn) or from day 20 on (Cdh2 and Jam3).

In [ 4] authors denoted the same problems not only for microarray data, but also for proteomic mass spectometry data.

Thus our analysis not only validates the microarray data but further shows that Aβ42 is a powerful regulator of certain mature miRNA sequences.

Understanding and quantifying the errors introduced by sequence mismatches is important, not only for handling microarray data, but also data from any high-throughput assay that makes use of duplex formation, for example sequence capture for regional sequencing [ 7- 10].