The VRNetzer platform enables interactive network analysis in Virtual Reality

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.

Overview of methods for characterization and visualization of a protein–protein interaction network in a multi-omics integration context

“…As the size and complexity of PPI networks increases, more efficient visualization algorithms are needed ( Chong, Wishart and Xia, 2019 ; Koutrouli et al, 2020 ). Augmented reality technologies and virtual reality (VR) remove the constraints of 2D/3D space constraints ( Pirch et al, 2021 ; Hütter et al, 2022 ). Moreover, the notable advances in the prediction of the structure of proteins from their sequence in amino acids with alphafold ( Jumper et al, 2021 ), which could lead to a revolution in the PPI prediction algorithm.…”

Bioinformatics and the Metaverse: Are We Ready?

“…VRNetzer ( Pirch et al, 2021 ) facilitates large biological and protein interaction network exploration, overcoming the often dense “hairballs” that are typical of such an analysis. ProteinVR ( Cassidy et al, 2020 ) is a web-based tool that can visualise PDB protein structures on multiple devices using WebXR that gives useful biological context and allows users to situate themselves in 3D space.…”

A Multi-scale Visual Analytics Approach for Exploring Biomedical Knowledge

“…Most existing visualization approaches support static overviews of the entire graph [18,20] and interactive views of focused subgraphs [1,11,40]. However, research has shown that the inherent multi-scale nature of biological graphs can only be fully appreciated when the entire range from local to global graph structures can be inspected continuously and interactively [32]. Some tools such as Reactome [35] strike a balance by displaying overviews of biological graphs as well as detailed views of selected subgraphs or pathways.…”