Supporting data for "iCAVE: an open source tool for visualizing biomolecular networks in 3D, stereoscopic 3D and immersive 3D"

Dataset type: Software
Data released on July 04, 2017

Liluashvili V; Kalayci S; Fluder E; Wilson M; Gabow A; Gümüş ZH (2017): Supporting data for "iCAVE: an open source tool for visualizing biomolecular networks in 3D, stereoscopic 3D and immersive 3D" GigaScience Database. http://dx.doi.org/10.5524/100288

DOI10.5524/100288

Visualizations of biomolecular networks assist in systems-level data exploration in many cellular processes. Data generated from high-throughput experiments increasingly inform these networks, yet current tools do not adequately scale with concomitant increase in their size and complexity. We present an open-source software platform, interactome-CAVE (iCAVE), for visualizing large and complex biomolecular interaction networks in three dimensions (3D). Users can explore networks (i) in 3D using a desktop; (ii) in stereoscopic 3D using 3D-vision glasses and a desktop; or (iii) in immersive 3D within a CAVE environment. iCAVE introduces 3D extensions of known 2D network layout, clustering, and edgebundling algorithms, as well as new 3D network layout algorithms. Furthermore, users can simultaneously query several built-in databases within iCAVE for network generation, or visualize their own networks (e.g. disease, drug, protein, metabolite). iCAVE has modular structure that allows rapid development by addition of algorithms, datasets or features without affecting other parts of the code. Overall, iCAVE is the first freely available open source tool that enables 3D (optionally stereoscopic or immersive) visualizations of complex, dense or multi-layered biomolecular networks. While primarily designed for researchers utilizing biomolecular networks, iCAVE can assist researchers in any field.

Additional details

Read the peer-reviewed publication(s):

(PubMed: 28814063)

Additional information:

http://research.mssm.edu/gumuslab/software.html





File NameSample IDData TypeFile FormatSizeRelease Date 
TextTEXT20.18 KB2017-06-27
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Mixed archiveTAR155.14 MB2017-07-07
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Funding body Awardee Award ID Comments
Concern Foundation ZH Gumus Conquer Cancer Now Award
Date Action
July 4, 2017 Dataset publish
November 13, 2017 Manuscript Link added : 10.1093/gigascience/gix054
November 9, 2022 Manuscript Link updated : 10.1093/gigascience/gix054