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ICPR
2004
IEEE
14 years 9 months ago
Feature Selection and Gene Clustering from Gene Expression Data
In this article we describe an algorithm for feature selection and gene clustering from high dimensional gene expression data. The method is based on measuring similarity between ...
D. Dutta Majumder, Pabitra Mitra
IJDMB
2006
125views more  IJDMB 2006»
13 years 8 months ago
Bi-level clustering of mixed categorical and numerical biomedical data
: Biomedical data sets often have mixed categorical and numerical types, where the former represent semantic information on the objects and the latter represent experimental result...
Bill Andreopoulos, Aijun An, Xiaogang Wang
BMCBI
2005
124views more  BMCBI 2005»
13 years 7 months ago
ErmineJ: Tool for functional analysis of gene expression data sets
Background: It is common for the results of a microarray study to be analyzed in the context of biologically-motivated groups of genes such as pathways or Gene Ontology categories...
Homin K. Lee, William Braynen, Kiran Keshav, Paul ...
BMCBI
2007
166views more  BMCBI 2007»
13 years 8 months ago
How to decide which are the most pertinent overly-represented features during gene set enrichment analysis
Background: The search for enriched features has become widely used to characterize a set of genes or proteins. A key aspect of this technique is its ability to identify correlati...
Roland Barriot, David J. Sherman, Isabelle Dutour
BMCBI
2006
186views more  BMCBI 2006»
13 years 8 months ago
Systematic gene function prediction from gene expression data by using a fuzzy nearest-cluster method
Background: Quantitative simultaneous monitoring of the expression levels of thousands of genes under various experimental conditions is now possible using microarray experiments....
Xiaoli Li, Yin-Chet Tan, See-Kiong Ng