Sentence examples for microarray data reviewed from inspiring English sources

A large number of algorithms based on machine learning and reverse engineering principles have been proposed to infer gene regulatory interactions from microarray data (reviewed in [ 13- 15]).

TRP analyzed microarray data, reviewed the literature to identify genes isolated from inner ear endorgans, executed the sequence similarity mappings, manually linked HGNC symbols to Xl-PSIDs, participated in data analysis, prepared and edited figures, and drafted the manuscript.

The pathway term FOSB was ranked highest by Literature Lab and highlighted as having a "strong" association; an increase in nuclear FOSB staining was subsequently confirmed with immunohistochemistry. Literature Lab is complementary to the increasingly prevalent pathway oriented approaches to the analysis of microarray data (Reviewed in [ 39]).

A variety of such statistical tests have been applied to microarray data (reviewed in [ 4, 16]); the challenge is to choose the numerator and denominator of the test statistic such that it makes the best use of all available data in order to get the most accurate determination of which genes are most likely to be regulated.

LAS generated the microarray data and reviewed the manuscript, JM validated expression levels of CRYBB2P1 and reviewed the manuscript, KM performed statistical analysis and reviewed the manuscript, CDS provided patient samples and clinical interpretation of the data, REE designed the study and wrote the manuscript.

MR provided microarray data and reviewed the manuscript.

A number of additional methods for dealing with spatial effects in expression microarray data are reviewed in Neuvial et al. [52].

Although numerous supervised or unsupervised machine learning techniques have been used for feature selection and sample classification of microarray data (for reviews see [33] [35]), classification performance appears to depend strongly on the dataset and less on the variable selection and classification methods [36].

SM was involved in the microarray data analysis and critically reviewed the manuscript.

Normalisation of array CGH data has generally involved the use of methods originally developed for normalising gene expression microarray data (for a review, see [51]).

Reviewing the microarray data on endometrial adenocarcinomas, there were a few DEGs that have previously been described in literatures and confirmed in this study [11] [17].