Two major problems related the unsupervised analysis of gene expression data are represented by the accuracy and reliability of the discovered clusters, and by the biological fact ...
The complexity, approximation and algorithmic issues of several clustering problems are studied. These non-traditional clustering problems arise from recent studies in microarray ...
Background: Data clustering analysis has been extensively applied to extract information from gene expression profiles obtained with DNA microarrays. To this aim, existing cluster...
Quantitative simultaneous monitoring of the expression levels of thousands of genes under various experimental conditions is now possible using microarray experiments. The resulti...
Background: One of the most commonly performed tasks when analysing high throughput gene expression data is to use clustering methods to classify the data into groups. There are a...
T. Ian Simpson, J. Douglas Armstrong, Andrew P. Ja...