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BIBE
2004
IEEE
120views Bioinformatics» more  BIBE 2004»
14 years 1 months ago
Identifying Projected Clusters from Gene Expression Profiles
In microarray gene expression data, clusters may hide in subspaces. Traditional clustering algorithms that make use of similarity measurements in the full input space may fail to ...
Kevin Y. Yip, David W. Cheung, Michael K. Ng, Kei-...
AIIA
2009
Springer
14 years 4 months ago
Ontology-Driven Co-clustering of Gene Expression Data
Abstract. The huge volume of gene expression data produced by microarrays and other high-throughput techniques has encouraged the development of new computational techniques to eva...
Francesca Cordero, Ruggero G. Pensa, Alessia Visco...
BMCBI
2006
127views more  BMCBI 2006»
13 years 9 months ago
Using local gene expression similarities to discover regulatory binding site modules
Background: We present an approach designed to identify gene regulation patterns using sequence and expression data collected for Saccharomyces cerevisae. Our main goal is to rela...
Bartek Wilczynski, Torgeir R. Hvidsten, Andriy Kry...
ICDM
2008
IEEE
193views Data Mining» more  ICDM 2008»
14 years 4 months ago
Multiplicative Mixture Models for Overlapping Clustering
The problem of overlapping clustering, where a point is allowed to belong to multiple clusters, is becoming increasingly important in a variety of applications. In this paper, we ...
Qiang Fu, Arindam Banerjee