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Bioinformatics Advance Access published online on April 28, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti475
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© The Author (2005). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oupjournals.org
Received April 1, 2005
Revised April 21, 2005
Accepted April 26, 2005

Applications note

ABNER: an open source tool for automatically tagging genes, proteins, and other entity names in text

Burr Settles 1*

1 Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI 52706, USA; Department of Biostatistics & Medical Informatics, University of Wisconsin-Madison, Madison, WI 52706, USA

* To whom correspondence should be addressed.
Burr Settles, E-mail: bsettles{at}cs.wisc.edu


  Abstract

Summary: 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 (CRFs) 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, cell line) trained on standard corpora, for which performance is roughly state of the art. It also includes a Java API allowing users to incorporate ABNER into their own systems and train models on new corpora.

Availability: ABNER is available as an executable Java archive and source code from http://www.cs.wisc.edu/~bsettles/abner/.


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