Help Login Create account

Data released on July 04, 2017

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

Fluder, E; Gabow, A; Gümüş, Z, H; Kalayci, S; Liluashvili, V; Wilson, M (2017): Supporting data for "iCAVE: an open source tool for visualizing biomolecular networks in 3D, stereoscopic 3D and immersive 3D" GigaScience Database. RIS BibTeX Text

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.

Contact Submitter

Related manuscripts:


Additional information:




  • Funding body - Concern Foundation
  • Comment - Conquer Cancer Now Award

Files: (FTP site) Table Settings


File Description
Sample ID
File Type
File Format
Release Date
Download Link
File Attributes

File NameSample IDFile TypeFile FormatSizeRelease Date 
Mixed archiveTAR155.14 MB2017-07-07
Mixed archiveTAR4.76 MB2017-06-27
ReadmeTEXT3.67 KB2017-06-27
TextTEXT60.84 KB2017-06-27
TextTEXT20.18 KB2017-06-27
TextTEXT620.18 KB2017-06-27
TextTEXT9.73 KB2017-06-27
TextTEXT7.36 KB2017-06-27
TextTEXT402.48 KB2017-06-27
TextTEXT692.92 KB2017-06-27
Displaying 1-10 of 15 File(s).



Other datasets you might like: