Abstract

Network biology has become crucial to understanding the complex structural characteristics of biological systems. Consequently, advanced visualization approaches are needed to support the investigation of such structures, and several network visualization tools have subsequently been developed to help researchers analyze intricate biological networks. While these tools support a range of analytical and interactive features, it is sometimes unclear to a data analyst or visualization designer which features are of most relevance to biologists. Thus, this study investigates and identifies essential factors for the visualization of complex biological networks using a mixed methodology approach. Based on the findings, essential factors were categorized as either generic and heuristic, where the former concern different analytical and interactive functionalities, such as an efficient layout, advanced search capabilities, plugin availability, graph analysis and user-friendliness, while the latter concern usability, such as information coding, flexibility, orientation and help.1Furthermore, the findings indicate that 12 of the 15 generic factors identified were moderately important, while all 10 heuristic factors identified herein were moderately important.

Full Text
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