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Ignet is a centrality- and ontology-based liteature discovery system for analyzing and visualizing human IFN-γ-mediated gene interaction network using all PubMed literature.

Interferon-gamma (IFN-γ) is vital in immune defense against bacterial and viral infections and tumor. It also regulates various immune responses that are often critical for induction of protective immunity generated by vaccines. Recently we have used a centrality-based literature discovery approach to study IFN-γ and vaccine-mediated gene interaction network. Our study identified indicated a generic IFNG network that contains 1060 genes and 26313 interactions among these genes. As a subset of this generic IFN-γ network, the vaccine-specific subnetwork contains 102 genes and 154 interactions.

Such literature-based discovery is novel. However, the analyzed data are not automatically updated, and the data are not easy to explore without a user-friendly web interface. In addition, the interaction types are not automatically retrieved by current system. To address these issues, we develop the web-based Ignet system. Ignet integrates the centrality-based literature mining approach with ontology analysis of interaction types using our newly developed Interaction Network Ontology (INO).

 



© 2012 University of Michigan. Ignet data and tools are freely available for public use.