Evaluation of clustering algorithms for gene expression data

Effective Clustering Algorithms for Gene Expression Data

Performance Analysis of Clustering Algorithms for Gene Expression Data

Microarray technology is a process that allows thousands of genes simultaneously monitor to various experimental conditions. It is used to identify the co-expressed genes in specific cells or tissues that are actively used to make proteins, This method is used to analysis the gene expression, an important task in bioinformatics research. Cluster analysis of gene expression data has proved to be...

Performance Analysis of Clustering Algorithms for Gene Expression Data

Microarray technology is a process that allows thousands of genes simultaneously monitor to various experimental conditions. It is used to identify the co-expressed genes in specific cells or tissues that are actively used to make proteins, This method is used to analysis the gene expression, an important task in bioinformatics research. Cluster analysis of gene expression data has proved to be...

Clustering Algorithms for Time Series Gene Expression in Microarray Data

illustrations, 75 numbered references. Clustering techniques are important for gene expression data analysis. However, efficient computational algorithms for clustering time-series data are still lacking. This work documents two improvements on an existing profile-based greedy algorithm for short time-series data; the first one is implementation of a scaling method on the pre-processing of the ...

Memory-Efficient Clustering Algorithms for Microarray Gene Expression Data

1 Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan 2 Department of Informatics, Graduate School of Information Science and Electrical Engineering, Kyushu University, 6-10-1 Hakozaki, Higashi-ku, Fukuoka 812-8581, Japan 3 Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 6110011, Japan ...