RingNet: An Interactive Platform for Multi-Modal Data Visualization in Networks

The exponential growth of data in biomedicine has created an urgent need for intuitive visualization tools. These tools must be able to effectively represent complex biological networks and remain accessible to domain experts without extensive computational training. Current network visualization approaches often require specialized programming skills and/or cannot handle the scale and complexity of modern biomedical datasets, which creates significant barriers to biological discovery. We develop RingNet, a web-based interactive visualization tool that integrates computational efficiency with flexible, user-driven exploration. This tool addresses the community’s need to visualize multi-modal datasets within a single, compact network representation, as well as identify patterns of interest in complex data. RingNet uses an R backend for network computation and coordinate optimization. This generates JSON data structures that feed into a JavaScript and HTML frontend, which provides real-time, interactive visualization functions. It offers dynamic layout adjustments, node and edge filtering, and customizable color schemes for representing data. It can export reproducible, publication-ready figures in SVG and PNG formats. In our case studies, we use RingNet to visualize breast cancer patients’ omics profiles in a gene regulatory network and a cell-to-cell communication network in atopic dermatitis. This demonstrates RingNet’s ability to reveal biological relationships across multiple data modalities. RingNet lowers the barrier to exploring, analyzing, and communicating data-driven findings, thereby accelerating research. Availability and Implementation The RingNet is available at https://ringnet.rd.tuni.fi and the source code for RingNet is accessible at https://github.com/laixn/ringnet . Highlights RingNet enables intuitive, interactive visualization of multi-modal networks without requiring advanced computational or programming expertise. RingNet has two functions: one to identify patterns in complex data at the node level, and the other to identify samples with homogeneous and heterogeneous profiles within network nodes. RingNet integrates efficient backend computation with real-time, flexible frontend exploration in a single, web-based framework. RingNet reveals cross-modal biological relationships and produces reproducible, publication-ready figures. Graphic abstract RingNet is a tool for visualizing multi-modal data in networks.