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论文类型：期刊论文

发表时间：2018-07-13

发表刊物：DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION

收录刊物：PubMed、SCIE、SSCI

卷号：2018

ISSN号：1758-0463

摘要：Automatically extracting protein-protein interactions (PPIs) from biomedical literature provides additional support for precision medicine efforts. This paper proposes a novel memory network-based model (MNM) for PPI extraction, which leverages prior knowledge about protein-protein pairs with memory networks. The proposed MNM captures important context clues related to knowledge representations learned from knowledge bases. Both entity embeddings and relation embeddings of prior knowledge are effective in improving the PPI extraction model, leading to a new state-of-the-art performance on the BioCreative VI PPI dataset. The paper also shows that multiple computational layers over an external memory are superior to long short-termmemory networks with the local memories.