Abstract
Networks provide a powerful representation of interacting components within complex systems, making them ideal for visually and analytically exploring big data. However, the size and complexity of many networks render static visualizations on typically-sized paper or screens impractical, resulting in proverbial ‘hairballs’. Here, we introduce a Virtual Reality (VR) platform that overcomes these limitations by facilitating the thorough visual, and interactive, exploration of large networks. Our platform allows maximal customization and extendibility, through the import of custom code for data analysis, integration of external databases, and design of arbitrary user interface elements, among other features. As a proof of concept, we show how our platform can be used to interactively explore genome-scale molecular networks to identify genes associated with rare diseases and understand how they might contribute to disease development. Our platform represents a general purpose, VR-based data exploration platform for large and diverse data types by providing an interface that facilitates the interaction between human intuition and state-of-the-art analysis methods.
| Original language | English |
|---|---|
| Article number | 2432 |
| Number of pages | 14 |
| Journal | Nature Communications |
| Volume | 12 |
| Issue number | 1 |
| DOIs | |
| Publication status | E-pub ahead of print - 23 Apr 2021 |
Funding
This work was supported by the Vienna Science and Technology Fund (WWTF) through projects VRG15-005 and NXT19-008, and by an Epic MegaGrant. We thank Harald H. H.W. Schmidt and Mathias Woidy for prototype testing. The authors affirm that the individual depicted in Figs. 1 and 2 provided informed consent for publication of their image.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 3 Good Health and Well-being
Austrian Fields of Science 2012
- 106041 Structural biology
Keywords
- HUMAN PHENOTYPE ONTOLOGY
- GENES
- PRIORITIZATION
- WALKING
- MODELS
- TOOL
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