Sentence examples for microarray papers we from inspiring English sources

Exact(1)

Guided by their popularity in applied microarray papers, we chose loess (cf. Yang et al., 2002) and quantile (cf. Bolstad et al., 2003) normalization.

Similar(59)

We excluded 19 of the listed microarray papers on the grounds that they looked at conditions that wild yeast populations would not be expected to encounter, leaving 11 papers suitable for analysis [ 41- 51].

However, of the thousands of DNA microarray papers published every year, few address the problem.

The majority of microarray papers published with regard to epileptogenesis involve chemical kindling.

Moreover, except for the statistical validation procedure, all the other algorithms are standard and have been used in published microarray papers.

Microarray gene expression databases like NCBI-GEO and EBI-ArrayExpress hold the raw data only for a very few of the 30 published Microarray papers that are listed in SAMMD.

Since the first DNA microarray paper demonstrated that microarray technology can monitor multiple gene expression profile in 1995 [1], DNA microarray technology has been developed steadily.

Please note that the terminology used to define the components of the array are derived from the original DNA microarray paper [ 62]; therefore, the target is that which is tethered to the array substrate and the probe is the labeled material in solution that hybridizes to the target.

For example, in the microarray experiments described in this paper we identified mkp1 as a gene induced after NGF withdrawal that could be a target of the MLK-JNK-c-Jun pathway.

DNA microarrays have been successfully used to study relative abundances of RNA and DNA, and in this paper we presented a microarray application for mapping insertion elements in microbial genomes.

In an effort to overcome the limitations of current reverse engineering algorithms and possible biases due to the microarray platform considered [16], in this paper we consider simultaneously five different algorithms and rely on datasets from two different platforms (cDNA and Affymetrix technologies).

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