Extracting chemical–protein interactions from literature using sentence structure analysis and feature engineering
Author:
Affiliation:
1. Department of Statistics, Florida State University, Tallahassee, FL, USA
2. School of Information, Florida State University, Tallahassee, FL, USA
3. Department of Geography, Florida State University, Tallahassee, FL, USA
Funder
National Institute of General Medical Sciences of the National Institute of Health
Publisher
Oxford University Press (OUP)
Subject
General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,Information Systems
Link
http://academic.oup.com/database/article-pdf/doi/10.1093/database/bay138/27436606/bay138.pdf
Reference49 articles.
1. All-paths graph kernel for protein–protein interaction extraction with evaluation of cross-corpus learning;Airola;BMC Bioinformatics,2008
2. PIPE: a protein–protein interaction passage extraction module for BioCreative challenge;Chang;Database,2016
3. Exploiting shallow linguistic information for relation extraction from biomedical literature;Giuliano
4. Protein–protein interaction extraction by leveraging multiple kernels and parsers;Miwa;Int. J. Med. Inform.,2009
5. Tree kernel-based protein–protein interaction extraction from biomedical literature;Qian;J. Biomed. Inform.,2012
Cited by 33 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Bioinformatics analysis of the potential biomarkers of Multiple Sclerosis and Guillain-Barré syndrome;2024-06-02
2. Deciphering the features and functions of serine/arginine protein kinases in bread wheat;Plant Gene;2024-06
3. BactInt: A domain driven transfer learning approach for extracting inter-bacterial associations from biomedical text;Computational Biology and Chemistry;2024-04
4. A hierarchical convolutional model for biomedical relation extraction;Information Processing & Management;2024-01
5. Bridging the Gap: A Hybrid Approach to Medical Relation Extraction Using Pretrained Language Models and Traditional Machine Learning;Journal of Advances in Information Technology;2024
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3