Background: Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or su...
Background: Microarray technology has made it possible to simultaneously measure the expression levels of large numbers of genes in a short time. Gene expression data is informati...
Abstract. Feature subset selection is an important subject when training classifiers in Machine Learning (ML) problems. Too many input features in a ML problem may lead to the so-...
The primary business model behind Web search is based on textual advertising, where contextually relevant ads are displayed alongside search results. We address the problem of sel...
Filip Radlinski, Andrei Z. Broder, Peter Ciccolo, ...
Background: Success of metabolomics as the phenotyping platform largely depends on its ability to detect various sources of biological variability. Removal of platform-specific so...
Marko Sysi-Aho, Mikko Katajamaa, Laxman Yetukuri, ...