Validating clustering for gene expression data
The remaining condition is used to assess the predictive power of the resulting clusters—meaningful...The remaining condition is used to assess the predictive power of the resulting clusters—meaningful clusters should exhibit less variation in the remaining condition than clusters formed by chance. “Validating Clusterings of Gene Expression Data.” In 2nd International Conference on Computer and Automation Engineering (ICCAE 2010), 1–245. This measure also useful to estimate missing gene expression levels, based the similarity information contained in a given clustering.
We provide a systematic framework for assessing the results of clustering algorithms.
As long as you attribute the data sets to the source, publish your adapted database with ODb L license, and keep the dataset open (don't use technical measures such as DRM to restrict access to the database).
You are free to copy, distribute and use the database; to produce works from the database; to modify, transform and build upon the database.
We found our quantitative measures of cluster quality to be positively correlated with external standards of cluster quality.