LinkedImm: a linked data graph database for integrating immunological data
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Updated: Oct 23, 2025

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques
Published on: January 2, 2011
Syed Ahmad Chan Bukhari1, Shrikant Pawar2, Jeff Mandell3
1Division of Computer Science, Mathematics and Science, Collins College of Professional Studies, St. John's University, New York, NY, USA.
Background:
Many systems biology studies leverage the integration of multiple data types (across different data sources) to offer a more comprehensive view of the biological system being studied. While SQL (Structured Query Language) databases are popular in the biomedical domain, NoSQL database technologies have been used as a more relationship-based, flexible and scalable method of data integration.
Results:
We have created a graph database integrating data from multiple sources. In addition to using a graph-based query language (Cypher) for data retrieval, we have developed a web-based dashboard that allows users to easily browse and plot data without the need to learn Cypher. We have also implemented a visual graph query interface for users to browse graph data. Finally, we have built a prototype to allow the user to query the graph database in natural language.
Conclusion:
We have demonstrated the feasibility and flexibility of using a graph database for storing and querying immunological data with complex biological relationships. Querying a graph database through such relationships has the potential to discover novel relationships among heterogeneous biological data and metadata.
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