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State-of-the-art methods for protein-protein interaction (PPI) extraction are primarily feature-based or kernel-based by leveraging lexical and syntactic information.
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Comparative experiments on learning information extractors for proteins and their interactions
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Yoshimasa Tsuruoka and Jun’ichi Tsujii. 2005 · 2005
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Semi-supervised classification for extracting protein interaction sentences using dependency parsing
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Sampo Pyysalo, Filip Ginter, Juho Heimonen, Jari Björne, Jorma Boberg, Jouni Järvinen, and Tapio Salakoski. 2007 · 2007
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Tree kernel-based relation extraction with context-sensitive structured parse tree information
Guodong Zhou, Min Zhang, Dong Hong, and Ji Qiaoming Zhu. 2007 · 2007
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All-paths graph kernel for protein-protein interaction extraction with evaluation of cross-corpus learning
Antti Airola, Sampo Pyysalo, Jari Björne, Tapio Pahikkala, Filip Ginter, and Tapio Salakoski. 2008 · 2008
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Overview of the protein-protein interaction annotation extraction task of BioCreative II
Martin Krallinger, Florian Leitner, Carlos Rodriguez-Penagos, Alfonso Valencia, et al. 2008 · 2008
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Comparative analysis of five protein-protein interaction corpora
Sampo Pyysalo, Antti Airola, Juho Heimonen, Jari Björne, Filip Ginter, and Tapio Salakoski. 2008 · 2008
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Extracting protein-protein interactions from text using rich feature vectors and feature selection
Sofie Van Landeghem, Yvan Saeys, Bernard De Baets, and Yves Van de Peer. 2008 · 2008
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David McClosky. 2009 · 2009
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Protein-protein interaction extraction by leveraging multiple kernels and parsers
Makoto Miwa, Rune Sætre, Yusuke Miyao, and Juníchi Tsujii. 2009a · 2009
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A rich feature vector for protein-protein interaction extraction from multiple corpora
Makoto Miwa, Rune Sætre, Yusuke Miyao, and Jun’ichi Tsujii. 2009b · 2009
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Xavier Glorot and Yoshua Bengio. 2010 · 2010
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Walk-weighted subsequence kernels for protein-protein interaction extraction
Seonho Kim, Juntae Yoon, Jihoon Yang, and Seog Park. 2010 · 2010
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A comprehensive benchmark of kernel methods to extract protein-protein interactions from literature
Community challenges in biomedical text mining over 10 years: success, failure and the future
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An extended dependency graph for relation extraction in biomedical texts
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Domonkos Tikk, Philippe Thomas, Peter Palaga, Jörg Hakenberg, and Ulf Leser. 2010 · 2010
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A hybrid approach to extract protein-protein interactions
Quoc-Chinh Bui, Sophia Katrenko, and Peter M. A. Sloot. 2011 · 2011
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A study on dependency tree kernels for automatic extraction of protein-protein interaction
Faisal Md. Chowdhury, Alberto Lavelli, and Alessandro Moschitti. 2011 · 2011
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Natural language processing (almost) from scratch
Ronan Collobert, Jason Weston, Léon Bottou, Michael Karlen, Koray Kavukcuoglu, and Pavel Kuksa. 2011 · 2011
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ImageNet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. 2012 · 2012
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Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013 · 2013
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Distributional semantics resources for biomedical text processing
Sampo Pyysalo, Filip Ginter, Hans Moen, Tapio Salakoski, and Sophia Ananiadou. 2013 · 2013
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Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, et al. 2016 · 2016
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A shortest dependency path based convolutional neural network for protein-protein relation extraction
Lei Hua and Chanqin Quan. 2016 · 2016
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Robert Leaman and Zhiyong Lu. 2016 · 2016
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Assessing the state of the art in biomedical relation extraction: overview of the BioCreative V chemical-disease relation (CDR) task
Chih-Hsuan Wei, Yifan Peng, Robert Leaman, Allan Peter Davis, Carolyn J. Mattingly, Jiao Li, Thomas C. Wiegers, and Zhiyong Lu. 2016 · 2016
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A protein-protein interaction extraction approach based on deep neural network
Zhehuan Zhao, Zhihao Yang, Hongfei Lin, Jian Wang, and Song Gao. 2016a · 2016
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Neural architectures for fine-grained entity type classification
Sonse Shimaoka, Pontus Stenetorp, Kentaro Inui, and Sebastian Riedel. 2017 · 2017
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