PPIExtractor: A Protein Interaction Extraction and Visualization System for Biomedical Literature
PPIExtractor: A Protein Interaction Extraction and Visualization System for Biomedical Literature
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PPIExtractor：生物医学文献的蛋白质相互作用提取和可视化系统
DOI：
10.1109/tnb.2013.2263837
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发表时间：
2013-09-01
影响因子：
3.9
通讯作者：
Lin, Hongfei
中科院分区：
文献类型：
--
作者：
Yang, Zhihao;Zhao, Zhehuan;Lin, Hongfei
蛋白质蛋白质相互作用（PPI）在细胞的结构和功能组织的各个方面起关键作用。关于它们的知识揭示了生物过程的分子机制。但是，有关蛋白质相互作用的生物医学文献量正在迅速增加，并且相互作用数据库策展人很难手动检测和策划蛋白质相互作用信息。在本文中，我们提出了一个称为ppiextractor的PPI提取系统，该系统自动从生物医学文本中提取PPI并对它们进行可视化。给定MEDLINE记录数据集，PPIEXTRACTOR首先将功能耦合概括（FCG）应用于文本中的标记蛋白质名称，接下来使用扩展语义相似性的方法来归一化，然后将基于功能的基于特征的基于特征的卷积树和图形内核来提取PPI，并最终可视化PPI网络。实验评估表明，ppiextractor可以在可比评估方面在DIP子集上实现最先进的性能。 ppiextractor可免费用于学术目的：http：//202.118.75.18:8080/ppiextractor/。
Protein-protein interactions (PPIs) play a key role in various aspects of the structural and functional organization of the cell. Knowledge about them unveils the molecular mechanisms of biological processes. However, the amount of biomedical literature regarding protein interactions is increasing rapidly and it is difficult for interaction database curators to detect and curate protein interaction information manually. In this paper, we present a PPI extraction system, termed PPIExtractor, which automatically extracts PPIs from biomedical text and visualizes them. Given a Medline record dataset, PPIExtractor first applies Feature Coupling Generalization (FCG) to tag protein names in text, next uses the extended semantic similarity-based method to normalize them, then combines feature-based, convolution tree and graph kernels to extract PPIs, and finally visualizes the PPI network. Experimental evaluations show that PPIExtractor can achieve state-of-the-art performance on a DIP subset with respect to comparable evaluations. PPIExtractor is freely available for academic purposes at: http://202.118.75.18:8080/PPIExtractor/.