187 search results - page 14 / 38 » Mining gene expression datasets using density-based clusteri... |
85
Voted
BMCBI
2008
14 years 9 months ago
2008
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...
102
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JBI
2004
14 years 11 months ago
2004
Microarray analysis using clustering algorithms can suffer from lack of inter-method consistency in assigning related gene-expression profiles to clusters. Obtaining a consensus s...
ICDM
2008
IEEE
15 years 4 months ago
2008
IEEE
Clustering problems often involve datasets where only a part of the data is relevant to the problem, e.g., in microarray data analysis only a subset of the genes show cohesive exp...
BMCBI
2004
14 years 9 months ago
2004
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...
90
Voted
WILF
2005
Springer
15 years 3 months ago
2005
Springer
Aim of this work is to apply a novel comprehensive machine learning tool for data mining to preprocessing and interpretation of gene expression data. Furthermore, some visualizatio...