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Welcome to Ignet! The Ignet (Integrated gene network) project is a centrality- and ontology-based liteature discovery system for analyzing and visualizing biological gene interaction networks using all PubMed literature papers. Currently Ignet focuses on the literature mining of human gene interaction networks.

The Ignet program is generated based on a literature mining strategy named CONDL, which represents the Centrality and Ontology-based Network Discovery using Literature data. The details about CONDL and its case study application have been described in the papers (Ozgur et al., 2011; Hur et al, 2012).

The CONDL strategy was initially applied to the literature mining of the Interferon-gamma (IFN-γ; Gene symbol: IFNG) and vaccine-mediated gene interaction networks. IFNG 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. Initially we 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 1,060 genes and 26,313 interactions among these genes (Reference: Ozgur et al, 2010). As a subset of this generic IFN-γ network, the vaccine-specific subnetwork contains 102 genes and 154 interactions. However, this literature mining strategy misses the identification of those sentences that include specifci vaccine names (e.g., BCG) without mentioning the words "vaccine", "vaccination", or their derivatives. Therefore, we used the VO hierarchy definitions to get more specific vaccine names and their relations, and used them for further literature mining. Our study found that more results were identified (Reference: Ozgur et al., 2011). Then such a CONDL strategy was proposed. Later we used the same CONDL strategy to study the fever and vaccine specific human gene interaction networks (Reference: Hur et al, 2012).

In addition, we have also developed an Interaction Network Ontology (INO). Such an ontology classifies different types of interactions in a hierarchical matter. By using INO, we expect to not only identify different gene-gene interactions, but also identify different interaction types.

It is noted that the Ignet database contains gene interactions identified with PubMed papers published unitl the end of 2011. We are still processing the literature papers published since 2012.

Ignet includes a dynamic query program Dignet, which allows a user to search for human gene interaction networks for a specific domain.

Your feedback is more than welcome and appreciated!



Ozgur A, Xiang Z, Radev D, He Y. Mining of vaccine-associated IFN-γ gene interaction networks using the Vaccine Ontology. Journal of Biomedical Semantics. 2011, 2(Suppl 2):S8. PMID: 21624163.

Hur J, Özgür A, Xiang Z, He Y. Identification of fever and vaccine-associated gene interaction networks using ontology-based literature mining. Journal of Biomedical Semantics. 2012, 3:18. PMID: 23256563.

© 2008-2013 University of Michigan. Ignet data and tools are freely available for public use.