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» A Repulsive Clustering Algorithm for Gene Expression Data
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ICASSP
2011
IEEE
12 years 11 months ago
A mutual information based approach for evaluating the quality of clustering
In this paper, a new method for evaluating the quality of clustering of genes is proposed based on mutual information criterion. Instead of using the conventional histogram-based ...
Shaikh Anowarul Fattah, Chia-Chun Lin, Sun-Yuan Ku...
BMCBI
2010
153views more  BMCBI 2010»
13 years 7 months ago
Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering
Background: Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or su...
Eva Freyhult, Mattias Landfors, Jenny Önskog,...
BIODATAMINING
2008
135views more  BIODATAMINING 2008»
13 years 7 months ago
Fast Gene Ontology based clustering for microarray experiments
Background: Analysis of a microarray experiment often results in a list of hundreds of diseaseassociated genes. In order to suggest common biological processes and functions for t...
Kristian Ovaska, Marko Laakso, Sampsa Hautaniemi
BMCBI
2006
155views more  BMCBI 2006»
13 years 7 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
2010
158views more  BMCBI 2010»
13 years 7 months ago
Validation of differential gene expression algorithms: Application comparing fold-change estimation to hypothesis testing
Background: Sustained research on the problem of determining which genes are differentially expressed on the basis of microarray data has yielded a plethora of statistical algorit...
Corey M. Yanofsky, David R. Bickel