关系抽取
计算机科学
关系(数据库)
基因
任务(项目管理)
关联规则学习
生物医学文本挖掘
命名实体识别
基因命名
数据挖掘
计算生物学
自然语言处理
人工智能
遗传学
生物
分类学(生物学)
文本挖掘
工程类
命名法
系统工程
植物
作者
Clement Essien,Fei He,Mark Hannink,Mihail Popescu,Dong Xu
标识
DOI:10.1109/bibm55620.2022.9995458
摘要
Relation Extraction (RE) is a critical task typically carried out after Named Entity recognition for identifying gene-gene association from scientific publication. Current state-of the-art tools have limited capacity as most of them only extract entity relations from abstract texts. The retrieved gene-gene relations typically do not cover gene regulatory relations. There still exists a lot of room for improvement. In this work, we propose GeREx, a transformer based RE tool for identifying gene regulatory relations from full texts by incorporating labeling from pathway figures. GeREx achieved an F1-Score of 83.45% when evaluated on an independent test dataset.
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