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» Identifying Projected Clusters from Gene Expression Profiles
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BIBE
2004
IEEE
120views Bioinformatics» more  BIBE 2004»
13 years 8 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-...
KDD
2003
ACM
148views Data Mining» more  KDD 2003»
14 years 5 months ago
A highly-usable projected clustering algorithm for gene expression profiles
Projected clustering has become a hot research topic due to its ability to cluster high-dimensional data. However, most existing projected clustering algorithms depend on some cri...
Kevin Y. Yip, David W. Cheung, Michael K. Ng
BMCBI
2006
153views more  BMCBI 2006»
13 years 4 months ago
Cancer diagnosis marker extraction for soft tissue sarcomas based on gene expression profiling data by using projective adaptive
Background: Recent advances in genome technologies have provided an excellent opportunity to determine the complete biological characteristics of neoplastic tissues, resulting in ...
Hiro Takahashi, Takeshi Nemoto, Teruhiko Yoshida, ...
BMCBI
2006
155views more  BMCBI 2006»
13 years 4 months ago
Analysis of promoter regions of co-expressed genes identified by microarray analysis
Background: The use of global gene expression profiling to identify sets of genes with similar expression patterns is rapidly becoming a widespread approach for understanding biol...
Srinivas Veerla, Mattias Höglund
BMCBI
2006
167views more  BMCBI 2006»
13 years 4 months ago
GOurmet: A tool for quantitative comparison and visualization of gene expression profiles based on gene ontology (GO) distributi
Background: The ever-expanding population of gene expression profiles (EPs) from specified cells and tissues under a variety of experimental conditions is an important but difficu...
Jason M. Doherty, Lynn K. Carmichael, Jason C. Mil...