In our previous study, we visualized microarray data of hepatocellular carcinoma (HCC) by using selforganizing-map, and investigated molecular signature representing the developme...
Clustering problems often involve datasets where only a part of the data is relevant to the problem, e.g., in microarray data analysis only a subset of the genes show cohesive exp...
There are many methods for assessing the quality of microarray data, but little guidance regarding what to do when defective data is identified. Depending on the scientific questio...
Permutation of class labels is a common approach to build null distributions for significance analyis of microarray data. It is assumed to produce random score distributions, which...
The problem of analyzing microarray data became one of important topics in bioinformatics over the past several years, and different data mining techniques have been proposed for ...
Image analysis is a crucial step in processing microarray data generated by gene expression studies, which have been used extensively in understanding the molecular mechanisms of ...
Yuhua Ding, Jacqueline Fairley, George J. Vachtsev...