Background: DNA microarrays are a powerful tool for monitoring the expression of tens of thousands of genes simultaneously. With the advance of microarray technology, the challeng...
Guoqing Lu, The V. Nguyen, Yuannan Xia, Michael Fr...
We propose an unsupervised methodology using independent component analysis (ICA) to cluster genes from DNA microarray data. Based on an ICA mixture model of genomic expression pa...
Background: High throughput microarray analyses result in many differentially expressed genes that are potentially responsible for the biological process of interest. In order to ...
Blaise T. F. Alako, Antoine Veldhoven, Sjozef van ...
Background: Clustering is a popular data exploration technique widely used in microarray data analysis. Most conventional clustering algorithms, however, generate only one set of ...
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...