Graphical models have become the basic framework for topic based probabilistic modeling. Especially models with latent variables have proved to be effective in capturing hidden str...
Background: Clustering methods are widely used on gene expression data to categorize genes with similar expression profiles. Finding an appropriate (dis)similarity measure is crit...
Kyungpil Kim, Shibo Zhang, Keni Jiang, Li Cai, In-...
Data clustering represents an important tool in exploratory data analysis. The lack of objective criteria render model selection as well as the identification of robust solutions...
Abstract. Metagenomics is the study of microbial communities sampled directly from their natural environment, without prior culturing. Among the computational tools recently develo...
We present algorithms for time-series gene expression analysis that permit the principled estimation of unobserved timepoints, clustering, and dataset alignment. Each expression p...
Ziv Bar-Joseph, Georg Gerber, David K. Gifford, To...