Recent advances in high-throughput technologies have enabled the profiling of multiple
layers of a biological system, including DNA sequence data (genomics), RNA expression …

Modelling relationship between entities in real‐world systems with a simple graph is a
standard approach. However, reality is better embraced as several interdependent …

Generating value from data requires the ability to find, access and make sense of datasets.
There are many efforts underway to encourage data sharing and reuse, from scientific …

Air pollution has become a serious public health problem for many cities around the world.
To find the causes of air pollution, the propagation processes of air pollutants must be …

Machine learning models are currently being deployed in a variety of real-world applications
where model predictions are used to make decisions about healthcare, bank loans, and …

For decades, researchers in information visualisation and graph drawing have focused on
developing techniques for the layout and display of very large and complex networks …

Network science is the field dedicated to the investigation and analysis of complex systems
via their representations as networks. We normally model such networks as graphs: sets of …

This work investigates and compares the performance of node-link diagrams, adjacency
matrices, and bipartite layouts for visualizing networks. In a crowd-sourced user study (), we …

Node-link diagrams are widely used to visualise networks. However, even the best network
layout algorithms ultimately result in 'hairball'visualisations when the graph reaches a …

From social networks to brain connectivity, ego networks are a simple yet powerful approach
to visualizing parts of a larger graph, ie those related to a selected focal node—the so-called …