![]() While these resources are valuable to capture the big picture in the field, get a sense of the available tools, and spot the strengths and the weaknesses of a tool of interest at a glance, no empirical feedback on the tools' scalability was obvious. Recent review articles discuss the challenges in the biological data visualization field and list a catalog of standalone and web-based visualization tools as well as the visual concepts they are implemented to serve. ![]() Visualization and exploration of biological networks at such scale are a computationally challenging task and many efforts in this direction have failed over the years. As such networks are characterized by different properties and topologies, graph theory comes to play a very important role by providing ways to efficiently store, analyze, and subsequently visualize them. ![]() Nowadays, biological repositories expand every day by hosting various entities such as proteins, genes, drugs, chemicals, ontologies, functions, articles, and the interactions between them, often leading to large-scale networks of thousands or even millions of nodes and connections. Health and natural sciences have become protagonists in the big-data world as high-throughput advances continuously contribute to the exponential growth of data volumes. ![]()
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