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» GenClust: A genetic algorithm for clustering gene expression...
122views more  BMCBI 2005»
13 years 6 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...
142views more  BMCBI 2008»
13 years 6 months ago
Genetic weighted k-means algorithm for clustering large-scale gene expression data
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
Fang-Xiang Wu
158views more  BMCBI 2004»
13 years 6 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, ...
141views Optimization» more  GECCO 2003»
13 years 11 months ago
Finding the Optimal Gene Order in Displaying Microarray Data
The rapid advances of genome-scale sequencing have brought out the necessity of developing new data processing techniques for enormous genomic data. Microarrays, for example, can g...
Seung-Kyu Lee, Yong-Hyuk Kim, Byung Ro Moon
164views Bioinformatics» more  APBC 2004»
13 years 7 months ago
Cluster Ensemble and Its Applications in Gene Expression Analysis
Huge amount of gene expression data have been generated as a result of the human genomic project. Clustering has been used extensively in mining these gene expression data to find...
Xiaohua Hu, Illhoi Yoo