Event extraction for post-translational modifications

Authors:
Tomoko Ohta;Sampo Pyysalo;Makoto Miwa;Jin-Dong Kim;Jun'ichi Tsujii
Affiliations:
University of Tokyo, Tokyo, Japan;University of Tokyo, Tokyo, Japan;University of Tokyo, Tokyo, Japan;University of Tokyo, Tokyo, Japan;University of Tokyo, Tokyo, Japan and University of Manchester, Manchester
Venue:
BioNLP '10 Proceedings of the 2010 Workshop on Biomedical Natural Language Processing
Year:
2010

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Abstract

We consider the task of automatically extracting post-translational modification events from biomedical scientific publications. Building on the success of event extraction for phosphorylation events in the BioNLP'09 shared task, we extend the event annotation approach to four major new post-transitional modification event types. We present a new targeted corpus of 157 PubMed abstracts annotated for over 1000 proteins and 400 post-translational modification events identifying the modified proteins and sites. Experiments with a state-of-the-art event extraction system show that the events can be extracted with 52% precision and 36% recall (42% F-score), suggesting remaining challenges in the extraction of the events. The annotated corpus is freely available in the BioNLP'09 shared task format at the GE-NIA project homepage.