| Summary: | <p>Abstract</p> <p>Background</p> <p>Negated biomedical events are often ignored by text-mining applications; however, such events carry scientific significance. We report on the development of BioN∅T, a database of negated sentences that can be used to extract such negated events.</p> <p>Description</p> <p>Currently BioN∅T incorporates ≈32 million negated sentences, extracted from over 336 million biomedical sentences from three resources: ≈2 million full-text biomedical articles in Elsevier and the PubMed Central, as well as ≈20 million abstracts in PubMed. We evaluated BioN∅T on three important genetic disorders: autism, Alzheimer's disease and Parkinson's disease, and found that BioN∅T is able to capture negated events that may be ignored by experts.</p> <p>Conclusions</p> <p>The BioN∅T database can be a useful resource for biomedical researchers. BioN∅T is freely available at <url>http://bionot.askhermes.org/.</url> In future work, we will develop semantic web related technologies to enrich BioN∅T.</p>
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