Current Protocols in BioinformaticsBioinformaticsPeer-reviewed journal article
Exploring biological networks in 3D, stereoscopic 3D and immersive 3D with iCAVE
Abstract
Biological networks are becoming increasingly large and complex, pushing the limits of existing 2D tools. iCAVE is an open source software tool for interactive visual explorations of large and complex networks in 3D, stereoscopic 3D or immersive 3D. It introduces new 3D network layout algorithms and 3D-extensions of popular 2D network layout, clustering and edge bundling algorithms to assists researchers in understanding the underlying patterns in large, multi-layered, clustered or complex networks. This protocol aims to guide new users on the basic functions of iCAVE for loading data, laying out networks (single or multi-layered), bundling edges, clustering networks, visualizing clusters, visualizing data attributes and saving output images or videos. It also provides examples on visualizing networks constrained in physical 3D space (e.g. proteins; neurons; brain). It is accompanied with a new version of iCAVE with an enhanced user interface and highlights new features useful for existing users.\n\nSignificance StatementNetwork representations assist in systems-level data exploration in many research fields, providing valuable insights. However, with the recent advances in experimental technologies, biological networks are becoming increasingly large and complex, necessitating new data visualization solutions. We have recently developed iCAVE (Liluashvili et al., 2017), an open?source software platform that enables 3D (optionally stereoscopic and or immersive) visualizations of complex, dense or multi?layered biological networks. Users can select from several new 3D network layout and clustering algorithms, bundle network edges and customize network attributes to reveal hidden structures within them. This protocol guides new users on loading, navigating, customizing and saving networks in iCAVE and is accompanied by an updated version of the software.
- research focus: software / tool
- research focus: benchmarking
- research focus: database / resource
- approach: experimental assay
- Citations
- 5
- FWCI
- 0.50
- Field percentile
- top 31%
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