ABNER: an open source tool for automatically tagging genes, proteins and other entity names in text. 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 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. Availability: ABNER is available as an executable Java archive and source code from http://www.cs.wisc.edu/ bsettles/abner/

References in zbMATH (referenced in 6 articles )

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  1. Fink, J. Lynn; Fernicola, Pablo; Chandran, Rahul; Parastatidis, Savas; Wade, Alex; Naim, Oscar; Quinn, Greg B.; Bourne, Philip E.: Word add-in for ontology recognition: semantic enrichment of scientific literature (2010) ioport
  2. Kabiljo, Renata; Clegg, Andrew B.; Shepherd, Adrian J.: A realistic assessment of methods for extracting gene/protein interactions from free text (2009) ioport
  3. Li, Yanpeng; Lin, Hongfei; Yang, Zhihao: Incorporating rich background knowledge for gene named entity classification and recognition (2009) ioport
  4. Shah, Nigam H.; Bhatia, Nipun; Jonquet, Clement; Rubin, Daniel L.; Chiang, Annie P.; Musen, Mark A.: Comparison of concept recognizers for building the open biomedical annotator (2009) ioport
  5. Wiegers, Thomas C.; Davis, Allan Peter; Cohen, K. Bretonnel; Hirschman, Lynette; Mattingly, Carolyn J.: Text mining and manual curation of chemical-gene-disease networks for the comparative toxicogenomics database (CTD) (2009) ioport
  6. Kim, Jin-Dong; Ohta, Tomoko; Tsujii, Jun’ichi: Corpus annotation for mining biomedical events from literature (2008) ioport