BioNet-XR: Biological Network Visualization Framework for Virtual Reality and Mixed Reality Environments
February 06, 2024 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Busra Senderin, Nurcan Tuncbag, Elif Surer
arXiv ID
2402.03946
Category
cs.MM: Multimedia
Citations
0
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Protein-protein interaction networks (PPIN) enable the study of cellular processes in organisms. Visualizing PPINs in extended reality (XR), including virtual reality (VR) and mixed reality (MR), is crucial for exploring subnetworks, evaluating protein positions, and collaboratively analyzing and discussing on networks with the help of recent technological advancements. Here, we present BioNet-XR, a 3D visualization framework, to visualize PPINs in VR and MR environments. BioNet-XR was developed with the Unity3D game engine. Our framework provides state-of-the-art methods and visualization features including teleportation between nodes, general and first-person view to explore the network, subnetwork construction via PageRank, Steiner tree, and all-pair shortest path algorithms for a given set of initial nodes. We used usability tests to gather feedback from both specialists (bioinformaticians) and generalists (multidisciplinary groups), addressing the need for usability evaluations of visualization tools. In the MR version of BioNet-XR, users can seamlessly transition to real-world environments and interact with protein interaction networks. BioNet-XR is highly modular and adaptable for visualization of other biological networks, such as metabolic and regulatory networks, and extension with additional network methods.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Multimedia
π
π
Old Age
R.I.P.
π»
Ghosted
Viewport-Adaptive Navigable 360-Degree Video Delivery
π
π
The Cartographer
A Comprehensive Survey on Cross-modal Retrieval
π
π
The Cartographer
An Overview of Cross-media Retrieval: Concepts, Methodologies, Benchmarks and Challenges
R.I.P.
π»
Ghosted
A Convolutional Neural Network Approach for Post-Processing in HEVC Intra Coding
R.I.P.
π»
Ghosted
Video Generation From Text
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted