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Extracting Protein Interactions from Text with the Unified AkaneRE Event Extraction System
July-September 2010 (vol. 7 no. 3)
pp. 442-453
ASCII Text
x 
 
Rune Sætre, Kazuhiro Yoshida, Makoto Miwa, Takuya Matsuzaki, Yoshinobu Kano, Jun'ichi Tsujii, "Extracting Protein Interactions from Text with the Unified AkaneRE Event Extraction System," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 7, no. 3, pp. 442-453, July-September, 2010.
 
 
BibTex
x
 
@article{ 10.1109/TCBB.2010.46,
author = {Rune Sætre and Kazuhiro Yoshida and Makoto Miwa and Takuya Matsuzaki and Yoshinobu Kano and Jun'ichi Tsujii},
title = {Extracting Protein Interactions from Text with the Unified AkaneRE Event Extraction System},
journal ={IEEE/ACM Transactions on Computational Biology and Bioinformatics},
volume = {7},
number = {3},
issn = {1545-5963},
year = {2010},
pages = {442-453},
doi = {http://doi.ieeecomputersociety.org/10.1109/TCBB.2010.46},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE/ACM Transactions on Computational Biology and Bioinformatics
TI - Extracting Protein Interactions from Text with the Unified AkaneRE Event Extraction System
IS - 3
SN - 1545-5963
SP442
EP453
EPD - 442-453
A1 - Rune Sætre,
A1 - Kazuhiro Yoshida,
A1 - Makoto Miwa,
A1 - Takuya Matsuzaki,
A1 - Yoshinobu Kano,
A1 - Jun'ichi Tsujii,
PY - 2010
KW - Text mining
KW - machine learning
KW - language parsing and understanding
KW - bioinformatics (genome or protein) databases.
VL - 7
JA - IEEE/ACM Transactions on Computational Biology and Bioinformatics
ER -
 
Rune Sætre, University of Tokyo, Tokyo
Kazuhiro Yoshida, University of Tokyo, Tokyo
Makoto Miwa, University of Tokyo, Tokyo
Takuya Matsuzaki, University of Tokyo, Tokyo
Yoshinobu Kano, University of Tokyo, Tokyo
Jun'ichi Tsujii, University of Tokyo, Tokyo and University of Manchester, Manchester
Currently, relation extraction (RE) and event extraction (EE) are the two main streams of biological information extraction. In 2009, the majority of these RE and EE research efforts were centered around the BioCreative II.5 Protein-Protein Interaction (PPI) challenge and the “BioNLP event extraction shared task.” Although these challenges took somewhat different approaches, they share the same ultimate goal of extracting bio-knowledge from the literature. This paper compares the two challenge task definitions, and presents a unified system that was successfully applied in both these and several other PPI extraction task settings. The AkaneRE system has three parts: A core engine for RE, a pool of modules for specific solutions, and a configuration language to adapt the system to different tasks. The core engine is based on machine learning, using either Support Vector Machines or Statistical Classifiers and features extracted from given training data. The specific modules solve tasks like sentence boundary detection, tokenization, stemming, part-of-speech tagging, parsing, named entity recognition, generation of potential relations, generation of machine learning features for each relation, and finally, assignment of confidence scores and ranking of candidate relations. With these components, the AkaneRE system produces state-of-the-art results, and the system is freely available for academic purposes at http://www-tsujii.is.s.u-tokyo.ac.jp/satre/akane/.

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Index Terms:
Text mining, machine learning, language parsing and understanding, bioinformatics (genome or protein) databases.
Citation:
Rune Sætre, Kazuhiro Yoshida, Makoto Miwa, Takuya Matsuzaki, Yoshinobu Kano, Jun'ichi Tsujii, "Extracting Protein Interactions from Text with the Unified AkaneRE Event Extraction System," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 7, no. 3, pp. 442-453, July-Sept. 2010, doi:10.1109/TCBB.2010.46
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