Networks are useful tools to represent and analyze interactions on a large, or genome-wide
scale and have therefore been widely used in biology. Many biological networks—such as …

During the last decade, while national homicide rates have remained flat, New York City has
experienced a second great crime decline, with gun violence declining by more than 50 …

Clustering molecular data into informative groups is a primary step in extracting robust
conclusions from big data. However, due to foundational issues in how they are defined and …

Node centrality measures are among the most commonly used analytical techniques for
networks. They have long helped analysts to identify “important” nodes that hold power in a …

Link prediction algorithms can help to understand the structure and dynamics of complex
systems, to reconstruct networks from incomplete data sets, and to forecast future …

Increasing social media use has transformed political participation by creating social cliques
and echo chambers, which involve interaction between like‐minded people. This article …

The usage of social networks shows a growing trend in recent years. Due to a large number
of online social networking users, there is a lot of data within these networks. Recently …

This paper presents a new computational framework for mapping state-sponsored
information operations into distinct strategic units. Utilizing a novel method called multi-view …

Here we study the semantic search and retrieval problem in biomedical digital libraries. First,
we introduce MedGraph, a knowledge graph embedding-based method that provides …

Scale-free networks, which play an important role in modelling human activities, are always
suffering from intentional attacks which have serious consequences on their functionality …