or k-means cluster analysis (Panel C), which reveals underlying patterns that can help identify subgroups in the data set. In microarray analysis, typically genes are sought that show patterns of ...

Resampling-based methods can address this last point, but results indicate that most clusterings in microarray data sets are unlikely to reflect reproducible patterns or patterns in the overall ...

Biologically relevant patterns of expression are typically ... Finally, as standards for publication of microarray experiments evolve, reporting data transformations is becoming as important ...

Microarrays are wonderful tools for seeing global patterns of gene expression under different conditions. Plenty of software exists to make sense of the data, but what if you want to correlate ...

Microarray technology ... The focus of Zhang's group is to look at automated detection of patterns and to devise rules for interpreting that data, using various types of analyses, including a ...

Visualization techniques can facilitate the extraction of meaningful patterns and trends by representing complex ... phylogenetic trees, microarray data, macromolecular structures, and networks.

Methods: TM4: a free, open-source system for microarray data management and analysis was used in order to identify expression patterns of interest in our cohort of renal cell carcinomas (RCC) (n=80).

We validated the model with data from an independent cohort ... microarray training set was validated in the microarray testing set, and the patterns of gene expression found on microarray ...

Perhaps the biggest challenge to microarray technology is standardization--ensuring that data collected from different microarray platforms can be accurately compared. Compounding this problem is the ...