RIscoper 2.0:一种深度学习工具,可以从文献中提取RNA生物医学关系句子
Hailong Zheng1, Linfu Xu1, Hailong Xie1
1Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, 510515 Guangzhou, China.
Computational and structural biotechnology journal
|April 16, 2024
概括
研究人员创建了一个大型的RNA生物医学关系库,并更新了RIscoper 2.0,一个深度学习工具,以从文献中提取这些关系,改善RNA研究的可访问性.
科学领域:
- 生物医学信息学 生物医学信息学
- 分子生物学分子生物学
- 计算生物学 计算生物学
背景情况:
- RNA在生物调节中至关重要,但其生物医学关系在研究中是分散的.
- 目前对RNA关系的文本挖掘工具是有限的.
研究的目的:
- 建立一个 RNA 生物医学关系的综合体.
- 增强一个深度学习工具 (RIScoper 2.0) 用于提取RNA关系.
- 为RNA研究提供可访问的工具.
主要方法:
- 从15,000多个生物医学文献中手动策划了超过3万个句子.
- 更新了基于BERT的工具Riscoper 2.0,集成文本分类和命名实体识别.
- 标注了大约10万个命名实体.
主要成果:
- 开发了一个可靠的RNA生物医学关系集体.
- 与其前身相比,Riscoper 2.0在关系提取方面表现出了优异的性能.
- 更新的工具可以识别新的RNA生物医学关系.
结论:
- 新的体和增强的RISCoper 2.0工具显著提升了RNA关系提取.
- 可访问的在线工具和数据资源有助于RNA研究.
- 这项工作支持发现新的RNA功能和相互作用.
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