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AI
2006
Springer
13 years 11 months ago
A New Profile Alignment Method for Clustering Gene Expression Data
We focus on clustering gene expression temporal profiles, and propose a novel, simple algorithm that is powerful enough to find an efficient distribution of genes over clusters. We...
Ataul Bari, Luis Rueda
BMCBI
2008
117views more  BMCBI 2008»
13 years 7 months ago
New resampling method for evaluating stability of clusters
Background: Hierarchical clustering is a widely applied tool in the analysis of microarray gene expression data. The assessment of cluster stability is a major challenge in cluste...
Irina Gana Dresen, Tanja Boes, Johannes Hüsin...
BMCBI
2004
158views more  BMCBI 2004»
13 years 7 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, ...
ICASSP
2008
IEEE
14 years 1 months ago
Probabilistic framework for gene expression clustering validation based on gene ontology and graph theory
Based on the correlation between expression and ontologydriven gene similarity, we incorporate functional annotations into gene expression clustering validation. A probabilistic f...
Yinyin Yuan, Chang-Tsun Li
BMCBI
2005
122views more  BMCBI 2005»
13 years 7 months ago
GenClust: A genetic algorithm for clustering gene expression data
Background: Clustering is a key step in the analysis of gene expression data, and in fact, many classical clustering algorithms are used, or more innovative ones have been designe...
Vito Di Gesù, Raffaele Giancarlo, Giosu&egr...