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» Clustering Genes Using Heterogeneous Data Sources
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BMCBI
2010
214views more  BMCBI 2010»
13 years 11 months ago
AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number
Background: Clustering the information content of large high-dimensional gene expression datasets has widespread application in "omics" biology. Unfortunately, the under...
Aaron M. Newman, James B. Cooper
KDD
2003
ACM
148views Data Mining» more  KDD 2003»
14 years 11 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
2004
158views more  BMCBI 2004»
13 years 10 months ago
Incremental genetic K-means algorithm and its application in gene expression data analysis
Background: In recent years, clustering algorithms have been effectively applied in molecular biology for gene expression data analysis. With the help of clustering algorithms suc...
Yi Lu, Shiyong Lu, Farshad Fotouhi, Youping Deng, ...
ISMB
2000
14 years 9 days ago
Genes, Themes, and Microarrays: Using Information Retrieval for Large-Scale Gene Analysis
The immensevolumeof data resulting from DNAmicroarray experiments, accompaniedby an increase in the numberof publications discussing gene-related discoveries, presents a majordata...
Hagit Shatkay, Stephen Edwards, W. John Wilbur, Ma...
NAR
2002
136views more  NAR 2002»
13 years 10 months ago
Gene Expression Omnibus: NCBI gene expression and hybridization array data repository
The Gene Expression Omnibus (GEO) project was initiated in response to the growing demand for a public repository for high-throughput gene expression data. GEO provides a flexible...
Ron Edgar, Michael Domrachev, Alex E. Lash