Unsupervised identification of patterns in microarray data has been a productive approach to uncovering relationships between genes and the biological process in which they are in...
Background: The amount of gene expression data in the public repositories, such as NCBI Gene Expression Omnibus (GEO) has grown exponentially, and provides a gold mine for bioinfo...
Rong Chen, Rohan Mallelwar, Ajit Thosar, Shivkumar...
Background: In class prediction problems using microarray data, gene selection is essential to improve the prediction accuracy and to identify potential marker genes for a disease...
Data clustering methods have been proven to be a successful data mining technique in the analysis of gene expression data. The Cluster affinity search technique (CAST) developed b...
Abdelghani Bellaachia, David Portnoy, Yidong Chen,...
Background: The high-density oligonucleotide microarray (GeneChip) is an important tool for molecular biological research aiming at large-scale detection of small nucleotide polym...
Leandro Hermida, Olivier Schaad, Philippe Demougin...