A fundamental task in various disciplines of science, including biology, is to find underlying
causal relations and make use of them. Causal relations can be seen if interventions are …

A central goal of systems biology is to elucidate the structural and functional architecture of
the cell. To this end, large and complex networks of molecular interactions are being rapidly …

Reconstructing gene regulatory networks from high-throughput data is a long-standing
challenge. Through the Dialogue on Reverse Engineering Assessment and Methods …

Background There is evidence that genes and their protein products are organized into
functional modules according to cellular processes and pathways. Gene co-expression …

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 …

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

Recognizing direct relationships between variables connected in a network is a pervasive
problem in biological, social and information sciences as correlation-based networks …

Motivation: Biclustering of transcriptomic data groups genes and samples simultaneously. It
is emerging as a standard tool for extracting knowledge from gene expression …

Motivation: The integration of multiple datasets remains a key challenge in systems biology
and genomic medicine. Modern high-throughput technologies generate a broad array of …

Biclustering extends the traditional clustering techniques by attempting to find (all)
subgroups of genes with similar expression patterns under to-be-identified subsets of …