Integrative Gene Interaction Network
Discover, analyze, and visualize gene-gene interaction networks from all PubMed literature. Powered by NLP, ontology, and AI.
Network Search
Build dynamic interaction networks from any PubMed query. Compute centrality scores and visualize results.
Gene
Explore interaction networks centered on individual genes. View neighbors, centrality rankings, and publications.
GenePair
Analyze specific gene pairs with BioBERT-powered interaction prediction and supporting evidence.
BioSummarAI
AI-powered summarization and conversational analysis of biomedical literature and gene interactions.
New in Ignet 2.0
Analyze Your Text
Paste a manuscript, abstract, or grant text. Ignet extracts gene interactions, builds networks, and discovers connections you may have missed.
COMING SOONExplore Networks
Browse curated gene interaction networks by research domain: immunology, cancer, vaccines, neurodegeneration, and more.
COMING SOONUser Accounts & BYOK
Save queries, view history, and bring your own LLM API key for extended AI-powered analysis. REST API access for developers.
About Ignet
Ignet mines all human genes defined in HUGO nomenclature and extracts gene-gene interactions from PubMed abstracts using SciMiner, a dictionary- and rule-based NLP system. Interactions are enriched with ontology annotations from INO (Interaction Network Ontology) and VO (Vaccine Ontology).
For each network, Ignet computes four centrality scores (Degree, Eigenvector, Closeness, and Betweenness) to identify key hub genes and their structural roles (Ozgur et al., 2008).
Cite Ignet
Ozgur A, Hur J, Xiang Z, Ong E, Radev D, and He Y. Ignet: A centrality and INO-based web system for analyzing and visualizing literature-mined networks. ICBO-2016 & BioCreative 2016, Oregon State University. (PDF)