title: ABNER: an open source tool for automatically tagging genes, proteins and other entity names in text.
abstract: ABNER (A Biomedical Named Entity Recognizer) is an open source software tool for molecular biology text mining. At its core is a machine learning system using conditional random fields with a variety of orthographic and contextual features. The latest version is 1.5, which has an intuitive graphical interface and includes two modules for tagging entities (e.g. protein and cell line) trained on standard corpora, for which performance is roughly state of the art. It also includes a Java application programming interface allowing users to incorporate ABNER into their own systems and train models on new corpora.
authors.affiliation: Department of Computer Sciences and Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison Madison, WI 52706, USA. bsettles@cs.wisc.edu
authors.forename: Burr
authors.initials: B
authors.lastname: Settles
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003628:Database Management Systems; D016206:Databases, Bibliographic; D005796:Genes / Q000235:genetics; D016247:Information Storage and Retrieval / Q000379:methods*; D009323:Natural Language Processing; D010506:Periodicals as Topic; D011381:Programming Languages; D011506:Proteins / Q000145:classification; D012984:Software; D014584:User-Computer Interface; D018875:Vocabulary, Controlled
chemical_list: D011506:Proteins