Abstract
Discovering the interactions between proteins mentioned in biomedical literature is one of the core topics of text mining in the life sciences. In this paper, we propose an interaction pattern generation approach to capture frequent PPI patterns in text. We also present an interaction pattern tree kernel method that integrates the PPI pattern with convolution tree kernel to extract protein-protein interactions. Empirical evaluations on LLL, IEPA, and HPRD50 corpora demonstrate that our method is effective and outperforms several well-known PPI extraction methods.
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Chang, YC., Su, YC., Chang, NW., Hsu, WL. (2014). An Interaction Pattern Kernel Approach for Protein-Protein Interaction Extraction from Biomedical Literature. In: Cheng, SM., Day, MY. (eds) Technologies and Applications of Artificial Intelligence. TAAI 2014. Lecture Notes in Computer Science(), vol 8916. Springer, Cham. https://doi.org/10.1007/978-3-319-13987-6_4
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DOI: https://doi.org/10.1007/978-3-319-13987-6_4
Publisher Name: Springer, Cham
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