BioTagger-GM: A Gene/Protein Name Recognition System | Zendy

Manabu Torii | Zendy; Zhipeng Hu | Zendy; Cathy Wu | Zendy; Hong Liu | Zendy

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BioTagger-GM: A Gene/Protein Name Recognition System

Author(s) -

Manabu Torii,

Zhipeng Hu,

Cathy Wu,

Hong Liu

Publication year - 2008

Publication title -

journal of the american medical informatics association

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.614

H-Index - 150

eISSN - 1527-974X

pISSN - 1067-5027

DOI - 10.1197/jamia.m2844

Subject(s) - computer science , artificial intelligence , named entity recognition , gene nomenclature , natural language processing , feature (linguistics) , terminology , heuristic , component (thermodynamics) , machine learning , domain (mathematical analysis) , information retrieval , task (project management) , biology , taxonomy (biology) , mathematical analysis , linguistics , philosophy , botany , physics , mathematics , management , nomenclature , economics , thermodynamics

Biomedical named entity recognition (BNER) is a critical component in automated systems that mine biomedical knowledge in free text. Among different types of entities in the domain, gene/protein would be the most studied one for BNER. Our goal is to develop a gene/protein name recognition system BioTagger-GM that exploits rich information in terminology sources using powerful machine learning frameworks and system combination.

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