OrganismTagger: detection, normalization and grounding of organism entities in biomedical documents | Zendy

a Naderi | Zendy; Thomas Kappler | Zendy; Christopher J. O. Baker | Zendy; René Witte | Zendy

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OrganismTagger: detection, normalization and grounding of organism entities in biomedical documents

Author(s) -

a Naderi,

Thomas Kappler,

Christopher J. O. Baker,

René Witte

Publication year - 2011

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btr452

Subject(s) - computer science , organism , information retrieval , taxonomy (biology) , natural language processing , precision and recall , named entity recognition , artificial intelligence , task (project management) , biology , paleontology , botany , management , economics

Semantic tagging of organism mentions in full-text articles is an important part of literature mining and semantic enrichment solutions. Tagged organism mentions also play a pivotal role in disambiguating other entities in a text, such as proteins. A high-precision organism tagging system must be able to detect the numerous forms of organism mentions, including common names as well as the traditional taxonomic groups: genus, species and strains. In addition, such a system must resolve abbreviations and acronyms, assign the scientific name and if possible link the detected mention to the NCBI Taxonomy database for further semantic queries and literature navigation.

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