Background: Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that a...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...
Background: Cluster analysis has been widely applied for investigating structure in bio-molecular data. A drawback of most clustering algorithms is that they cannot automatically ...
In recent years, many networks have become available for analysis, including social networks, sensor networks, biological networks, etc. Graph clustering has shown its effectivenes...
: The traditional latent class analysis (LCA) uses a mixture model with binary responses on each subject that are independent conditional on cluster membership. However, in many pr...
Background: Gene clustering has been widely used to group genes with similar expression pattern in microarray data analysis. Subsequent enrichment analysis using predefined gene s...
Tae-Min Kim, Yeun-Jun Chung, Mun-Gan Rhyu, Myeong ...