title: What makes a gene name? Named entity recognition in the biomedical literature.
abstract: The recognition of biomedical concepts in natural text (named entity recognition, NER) is a key technology for automatic or semi-automatic analysis of textual resources. Precise NER tools are a prerequisite for many applications working on text, such as information retrieval, information extraction or document classification. Over the past years, the problem has achieved considerable attention in the bioinformatics community and experience has shown that NER in the life sciences is a rather difficult problem. Several systems and algorithms have been devised and implemented. In this paper, the problems and resources in NER research are described, the principal algorithms underlying most systems sketched, and the current state-of-the-art in the field surveyed.
authors.affiliation: Department for Computer Science, Humboldt-Universität zu Berlin, Rudower Chaussee 25, Germany. leser@informatik.hu-berlin.de
authors.forename: Ulf
authors.initials: U
authors.lastname: Leser
authors.forename: Jörg
authors.initials: J
authors.lastname: Hakenberg
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D035843:Biomedical Research / Q000145:classification*; D003628:Database Management Systems; D016208:Databases, Factual; D005796:Genes / Q000235:genetics*; D016247:Information Storage and Retrieval / Q000379:methods*; D009323:Natural Language Processing; D010506:Periodicals as Topic; D009626:Terminology as Topic