In recent years, network analysis has been applied to identify and analyse patterns of
statistical association in multivariate psychological data. In these approaches, network …

Detecting a community in a network is a matter of discerning the distinct features and
connections of a group of members that are different from those in other communities. The …

Large-scale single-cell RNA sequencing (scRNA-seq) data sets that are produced in
different laboratories and at different times contain batch effects that may compromise the …

Community detection in networks is one of the most popular topics of modern network
science. Communities, or clusters, are usually groups of vertices having higher probability of …

Single-cell RNA-seq quantifies biological heterogeneity across both discrete cell types and
continuous cell transitions. Partition-based graph abstraction (PAGA) provides an …

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 …

The spread of fake news on social media became a public concern in the United States after
the 2016 presidential election. We examined exposure to and sharing of fake news by …

We propose a simple method to extract the community structure of large networks. Our
method is a heuristic method that is based on modularity optimization. It is shown to …

Background Understanding the interaction among different species within a community and
their responses to environmental changes is a central goal in ecology. However, defining …

We consider the problem of detecting communities or modules in networks, groups of
vertices with a higher-than-average density of edges connecting them. Previous work …