Ranking SVM for Multiple Kernels Output Combination in Protein-Protein Interaction Extraction from Biomedical Literature

被引：0

作者：

Yang, Zhihao ^{[1
]}

Lin, Yuan ^{[1
]}

Wu, Jiajin ^{[1
]}

Tang, Nan ^{[1
]}

Lin, Hongfei ^{[1
]}

Li, Yanpeng ^{[1
]}

机构：

[1] Dalian Univ Technol, Dept Comp Sci & Engn, Dalian, Peoples R China

来源：

2010 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE | 2010年

关键词：

Protein-protein interaction; Support Vector Machines; Multiple kernels learning;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Knowledge about protein-protein interactions unveils the molecular mechanisms of biological processes. This paper presents a multiple kernels learning-based approach to automatically extracting protein-protein interactions from biomedical literature. Experimental evaluations show that our approach can achieve state-of-the-art performance with respect to comparable evaluations, with 64.88% F-score and 88.02% area under the receiver operating characteristics curve (AUC) on the AImed corpus.

引用

页码：595 / 598

页数：4

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