bioRxivBioinformatics
iCAVE: an open source tool for immersive 3D visualization of complex biomolecular interaction networks
Vaja Liluashvili, Selim Kalayci, Eugene Flouder, Manda Wilson, Aaron Gabow, Zeynep H. Gümüş
Abstract
Visualizations of biomolecular networks assist in systems-level data exploration in myriad cellular processes in health and disease. While these networks are increasingly informed by data generated from high-throughout (HT) experiments, current tools do not adequately scale with concomitant increase in their size and complexity. We present an open-source software platform, interactome-CAVE, (iCAVE), that leverages stereoscopic (3D) immersive display technologies for visualizing complex biomolecular interaction networks. Users can explore networks (i) in 3D in any computer and (ii) in immersive 3D in any computer with an appropriate graphics card as well as in CAVE environments. iCAVE includes new 3D network layout algorithms in addition to extensions of known 2D network layout, clustering and edge-bundling algorithms to the 3D space, to assist in understanding the underlying structures in large, dense, layered or clustered networks. Users can perform simultaneous queries of several databases within iCAVE or visualize their own networks (e.g. disease, drug, protein, metabolite, phenotype, genotype) utilizing directionality, weight or other properties by using different property settings. iCAVE has modular structure to allow rapid development by the addition of algorithms, datasets or features without affecting other parts of the code. Overall, iCAVE is a freely available open source tool to help gain novel insights from complex HT datasets.
- assay: protein sequence
- research focus: software / tool
- research focus: dimensionality reduction
- research focus: clustering
- approach: experimental assay
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