| Qian Weizhong（钱伟中）,Ungar Lyle,Qin Zhiguang,Fu Chong.[J].高技术通讯(英文),2011,17(1):32~38 |
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| A hybrid method for extraction of protein-protein interactions from literature |
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| DOI： |
| 中文关键词: |
| 英文关键词: protein-protein interaction(PPI), machine learning, pattern learning, maximum entropy, part of speech |
| 基金项目: |
| Author Name | Affiliation | | Qian Weizhong（钱伟中） | | | Ungar Lyle | | | Qin Zhiguang | | | Fu Chong | |
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| 中文摘要: |
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| 英文摘要: |
| In this work, a hybrid method is proposed to eliminate the limitations of traditional protein-protein interactions (PPIs) extraction methods, such as pattern learning and machine learning. Each sentence from the biomedical literature containing a protein pair describes a PPI which is predicted by first learning syntax patterns typical of PPIs from training corpus and then using their presence as features, along with bag-of-word features in a maximum entropy model. Tested on the BioCreAtIve corpus, the PPIs extraction method, which achieved a precision rate of 64%, recall rate of 60%, improved the performance in terms of F1 value by 11% compared with the component pure pattern-based and bag-of-word methods. The results on this test set were also compared with other three extraction methods and found to improve the performance remarkably. |
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