Microorganisms including bacteria, fungi, viruses, protists and archaea live as communities
in complex and contiguous environments. They engage in numerous inter-and intra …

A graphical model is a statistical model that is associated with a graph whose nodes
correspond to variables of interest. The edges of the graph reflect allowed conditional …

A graph is one of important mathematical tools to describe ubiquitous relations. In the
classical graph theory and some applications, graphs are generally provided in advance, or …

Overfitting describes the phenomenon where a highly predictive model on the training data
generalizes poorly to future observations. It is a common concern when applying machine …

Network modeling of high-dimensional time series data is a key learning task due to its
widespread use in a number of application areas, including macroeconomics, finance, and …

The eyes are our windows to the brain. There are differences in brain activity between
people who have their eyes closed (EC) and eyes open (EO). Previous studies focused on …

Gaussian graphical models (GGMs) provide a framework for modeling conditional
dependencies in multivariate data. In this tutorial, we provide an overview of GGM theory …

Motivation Understanding how gene regulatory networks change under different cellular
states is important for revealing insights into network dynamics. Gaussian graphical models …

Brain network analysis can help reveal the pathological basis of neurological disorders and
facilitate automated diagnosis of brain diseases, by exploring connectivity patterns in the …

Motivation Joint reconstruction of multiple gene regulatory networks (GRNs) using gene
expression data from multiple tissues/conditions is very important for understanding …