A large number of clustering approaches have been proposed for the analysis of gene
expression data obtained from microarray experiments. However, the results from the …

Network inference, which is the reconstruction of biological networks from high-throughput
data, can provide valuable information about the regulation of gene expression in cells …

Many vaccines induce protective immunity via antibodies. Systems biology approaches
have been used to determine signatures that can be used to predict vaccine-induced …

A critical step in the analysis of large genome-wide gene expression datasets is the use of
module detection methods to group genes into co-expression modules. Because of …

As a prolific research area in data mining, subspace clustering and related problems
induced a vast quantity of proposed solutions. However, many publications compare a new …

Mixture models have been around for over 150 years, and they are found in many branches
of statistical modelling, as a versatile and multifaceted tool. They can be applied to a wide …

Motivation: In recent years, there have been various efforts to overcome the limitations of
standard clustering approaches for the analysis of gene expression data by grou** genes …

In gene expression data, a bicluster is a subset of the genes exhibiting consistent patterns
over a subset of the conditions. We propose a new method to detect significant biclusters in …

Next-generation DNA sequencing technologies are enabling genome-wide measurements
of somatic mutations in large numbers of cancer patients. A major challenge in the …

Biclustering has become a popular technique for the study of gene expression data,
especially for discovering functionally related gene sets under different subsets of …