LINNAEUS: A species name identification system for biomedical literature
Identifieur interne : 000603 ( Main/Exploration ); précédent : 000602; suivant : 000604LINNAEUS: A species name identification system for biomedical literature
Auteurs : Martin Gerner [Royaume-Uni] ; Goran Nenadic [Royaume-Uni] ; Casey M. Bergman [Royaume-Uni]Source :
- BMC Bioinformatics [ 1471-2105 ] ; 2010.
Abstract
The task of recognizing and identifying species names in biomedical literature has recently been regarded as critical for a number of applications in text and data mining, including gene name recognition, species-specific document retrieval, and semantic enrichment of biomedical articles.
In this paper we describe an open-source species name recognition and normalization software system, LINNAEUS, and evaluate its performance relative to several automatically generated biomedical corpora, as well as a novel corpus of full-text documents manually annotated for species mentions. LINNAEUS uses a dictionary-based approach (implemented as an efficient deterministic finite-state automaton) to identify species names and a set of heuristics to resolve ambiguous mentions. When compared against our manually annotated corpus, LINNAEUS performs with 94% recall and 97% precision at the mention level, and 98% recall and 90% precision at the document level. Our system successfully solves the problem of disambiguating uncertain species mentions, with 97% of all mentions in PubMed Central full-text documents resolved to unambiguous NCBI taxonomy identifiers.
LINNAEUS is an open source, stand-alone software system capable of recognizing and normalizing species name mentions with speed and accuracy, and can therefore be integrated into a range of bioinformatics and text-mining applications. The software and manually annotated corpus can be downloaded freely at
Url:
DOI: 10.1186/1471-2105-11-85
PubMed: 20149233
PubMed Central: 2836304
Affiliations:
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Le document en format XML
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<front><div type="abstract" xml:lang="en"><sec><title>Background</title>
<p>The task of recognizing and identifying species names in biomedical literature has recently been regarded as critical for a number of applications in text and data mining, including gene name recognition, species-specific document retrieval, and semantic enrichment of biomedical articles.</p>
</sec>
<sec><title>Results</title>
<p>In this paper we describe an open-source species name recognition and normalization software system, LINNAEUS, and evaluate its performance relative to several automatically generated biomedical corpora, as well as a novel corpus of full-text documents manually annotated for species mentions. LINNAEUS uses a dictionary-based approach (implemented as an efficient deterministic finite-state automaton) to identify species names and a set of heuristics to resolve ambiguous mentions. When compared against our manually annotated corpus, LINNAEUS performs with 94% recall and 97% precision at the mention level, and 98% recall and 90% precision at the document level. Our system successfully solves the problem of disambiguating uncertain species mentions, with 97% of all mentions in PubMed Central full-text documents resolved to unambiguous NCBI taxonomy identifiers.</p>
</sec>
<sec><title>Conclusions</title>
<p>LINNAEUS is an open source, stand-alone software system capable of recognizing and normalizing species name mentions with speed and accuracy, and can therefore be integrated into a range of bioinformatics and text-mining applications. The software and manually annotated corpus can be downloaded freely at <ext-link ext-link-type="uri" xlink:href="http://linnaeus.sourceforge.net/">http://linnaeus.sourceforge.net/</ext-link>
.</p>
</sec>
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</listBibl>
</div1>
</back>
</TEI>
<affiliations><list><country><li>Royaume-Uni</li>
</country>
<region><li>Angleterre</li>
<li>Grand Manchester</li>
</region>
<settlement><li>Manchester</li>
</settlement>
<orgName><li>Université de Manchester</li>
</orgName>
</list>
<tree><country name="Royaume-Uni"><region name="Angleterre"><name sortKey="Gerner, Martin" sort="Gerner, Martin" uniqKey="Gerner M" first="Martin" last="Gerner">Martin Gerner</name>
</region>
<name sortKey="Bergman, Casey M" sort="Bergman, Casey M" uniqKey="Bergman C" first="Casey M" last="Bergman">Casey M. Bergman</name>
<name sortKey="Nenadic, Goran" sort="Nenadic, Goran" uniqKey="Nenadic G" first="Goran" last="Nenadic">Goran Nenadic</name>
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</affiliations>
</record>
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