Increased availability of high-throughput technologies has generated an ever-growing
number of omics data that seek to portray many different but complementary biological …

A random field is the representation of the joint probability distribution for a set of random
variables. Markov fields, in particular, have a long standing tradition as the theoretical …

Existing methods for gene regulatory network (GRN) inference rely on gene expression data
alone or on lower resolution bulk data. Despite the recent integration of chromatin …

Simple Summary Aberrant epigenetic modifications in oncogenic pathways can lead to the
onset of different cancers. This study aims to explore the role of differential DNA methylation …

Methods We conducted a cross-sectional study with 1,230 Greek adults (67.6% females,
32.4% males), using a network analysis to assess the relationships among positive …

Abstract Accurate context-specific Gene Regulatory Networks (GRNs) inference from
genomics data is a crucial task in computational biology. However, existing methods face …

Background Applying directed acyclic graph (DAG) models to proteogenomic data has been
shown effective for detecting causal biomarkers of complex diseases. However, there …

Many biomedical studies collect data of mixed types of variables from multiple groups of
subjects. Some of these studies aim to find the group‐specific and the common variation …

In several application areas, discretized variables represent an underlying continuous
variable. For example, the level of certain medical measures can be 'low','medium'or 'high' …

In single-cell genomics, we can simultaneously assay hundreds of thousands of cells, their
molecular contents, and how they respond to perturbation, from genetic knockouts to …