In this topical review we consider stochastic processes under resetting, which have attracted
a lot of attention in recent years. We begin with the simple example of a diffusive particle …

Biological networks are powerful resources for the discovery of genes and genetic modules
that drive disease. Fundamental to network analysis is the concept that genes underlying the …

Recommender systems use past behaviors of users to suggest items. Most tend to offer
items similar to the items that a target user has indicated as interesting. As a result, users …

Through the developments of Omics technologies and dissemination of large-scale
datasets, such as those from The Cancer Genome Atlas, Alzheimer's Disease Neuroimaging …

Transfer learning has been demonstrated to be effective for many real-world applications as
it exploits knowledge present in labeled training data from a source domain to enhance a …

The modern science of networks has brought significant advances to our understanding of
complex systems. One of the most relevant features of graphs representing real systems is …

We study experimentally and theoretically the optimal mean time needed by a free diffusing
Brownian particle to reach a target at a distance L from an initial position in the presence of …

Background Drug-target interaction prediction is of great significance for narrowing down the
scope of candidate medications, and thus is a vital step in drug discovery. Because of the …

Drug–target interaction (DTI) is an important step in drug discovery. Although there are many
methods for predicting drug targets, these methods have limitations in using discrete or …

How can we estimate the importance of nodes in a knowledge graph (KG)? A KG is a multi-
relational graph that has proven valuable for many tasks including question answering and …