BioN∅T: A searchable database of biomedical negated sentences
<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 neg...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2011-10-01
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| Series: | BMC Bioinformatics |
| Online Access: | http://www.biomedcentral.com/1471-2105/12/420 |
| _version_ | 1818788588700041216 |
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| author | Agarwal Shashank Yu Hong Kohane Issac |
| author_facet | Agarwal Shashank Yu Hong Kohane Issac |
| author_sort | Agarwal Shashank |
| collection | DOAJ |
| description | <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> |
| first_indexed | 2024-12-18T14:26:03Z |
| format | Article |
| id | doaj.art-038681aa52ae4a3eaab54ef0c0c068f7 |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-12-18T14:26:03Z |
| publishDate | 2011-10-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-038681aa52ae4a3eaab54ef0c0c068f72022-12-21T21:04:43ZengBMCBMC Bioinformatics1471-21052011-10-0112142010.1186/1471-2105-12-420BioN∅T: A searchable database of biomedical negated sentencesAgarwal ShashankYu HongKohane Issac<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>http://www.biomedcentral.com/1471-2105/12/420 |
| spellingShingle | Agarwal Shashank Yu Hong Kohane Issac BioN∅T: A searchable database of biomedical negated sentences BMC Bioinformatics |
| title | BioN∅T: A searchable database of biomedical negated sentences |
| title_full | BioN∅T: A searchable database of biomedical negated sentences |
| title_fullStr | BioN∅T: A searchable database of biomedical negated sentences |
| title_full_unstemmed | BioN∅T: A searchable database of biomedical negated sentences |
| title_short | BioN∅T: A searchable database of biomedical negated sentences |
| title_sort | bion∅t a searchable database of biomedical negated sentences |
| url | http://www.biomedcentral.com/1471-2105/12/420 |
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