An interaction pattern kernel approach for protein-protein interaction extraction from biomedical literature

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 wellknown PPI extraction methods.