Knowledge-Graph-UI (KG-UI) is an open-source web-based user interface built for KGs stored in Neo4j. The UI features Cypher queries for viewing immediate neighbors as well as shortest paths between two entities. Additionally, the API can be extended to add other functions such as enrichment analy...
Overview
KG-UI is an innovative knowledge graph user interface designed specifically for Neo4j knowledge graph databases, making it a valuable tool for bioinformatics applications. With its intuitive design and robust capabilities, it provides users the resources they need to effectively manage and interact with complex datasets.
Whether you’re a researcher looking to harness the power of knowledge graphs or a developer seeking to integrate this technology into your applications, KG-UI offers an accessible starting point with its comprehensive Jupyter notebooks that guide users through various processes, from creating assertions to setting up the interface.
Features
- User-Friendly Interface: KG-UI simplifies the interaction with Neo4j databases, providing a clean and intuitive layout for easier navigation and data manipulation.
- Comprehensive Tutorials: The included Jupyter notebooks cover essential topics such as Cypher language, assertions creation, and user interface setup, making it easy for users of all skill levels to get started.
- Local Deployment: Running the interface locally is straightforward, requiring simple commands to launch the application for immediate access via a web browser.
- Kubernetes Installation: Seamlessly deploy KG-UI with Kubernetes, enabling users to scale their operations efficiently and manage containerized applications with ease.
- Customization Options: Users can tailor the user interface to fit their specific needs, with detailed examples provided for various customization options.
- Video Tutorials Available: A series of video tutorials help users visualize key concepts and practices, making learning more engaging and effective.
