PIPE: a protein–protein interaction passage extraction module for BioCreative challenge
| Autor: | Yu Chen Su, Chien Chin Chen, Yung-Chun Chang, Chun Han Chu, Wen-Lian Hsu |
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| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
Computer science computer.software_genre General Biochemistry Genetics and Molecular Biology Field (computer science) 03 medical and health sciences 0302 clinical medicine Text mining Animals Data Mining Humans Biocurator 030212 general & internal medicine business.industry Proteins Convolution (computer science) Task (computing) Tree (data structure) 030104 developmental biology Kernel method Original Article Data mining Tree kernel General Agricultural and Biological Sciences business computer Information Systems |
| Zdroj: | Database: The Journal of Biological Databases and Curation |
| ISSN: | 1758-0463 |
| Popis: | Identifying the interactions between proteins mentioned in biomedical literatures is one of the frequently discussed topics of text mining in the life science field. In this article, we propose PIPE, an interaction pattern generation module used in the Collaborative Biocurator Assistant Task at BioCreative V (http://www.biocreative.org/) to capture frequent protein-protein interaction (PPI) patterns within text. We also present an interaction pattern tree (IPT) kernel method that integrates the PPI patterns with convolution tree kernel (CTK) to extract PPIs. Methods were evaluated on LLL, IEPA, HPRD50, AIMed and BioInfer corpora using cross-validation, cross-learning and cross-corpus evaluation. Empirical evaluations demonstrate that our method is effective and outperforms several well-known PPI extraction methods. Database URL |
| Databáze: | OpenAIRE |
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