通过从文学中绘制生物实体 (MaBEL) 来搜索与疾病相关的基因
Gratchela Dutra Rodrigues1, Gabriel Liston de Menek1, Darling de Andrade Lourenço1
1Centro de Desenvolvimento Tecnológico, Campus Universitário, S / N - Capão do Leão, Rio Grande do Sul 96160-000, Brazil.
Computational biology and chemistry
|February 21, 2026
概括
MaBEL (从文学中绘制生物学实体) 是一个文本挖掘平台,可以有效地从各种科学文献中识别与疾病相关的基因. 它通过分析大量数据,加速发现潜在的治疗点.
科学领域:
- 生物医学信息学 生物医学信息学
- 计算生物学 计算生物学
- 文本挖掘 (Text Mining) 是一个很好的方法.
背景情况:
- 生物医学文献的指数式增长给识别与疾病相关的基因和治疗点带来了挑战.
- 现有的文本挖掘系统通常依赖于单一的数据源,限制了全面的分析.
研究的目的:
- 推出MaBEL (从文学中绘制生物实体的地图),一个可扩展和适应的文本挖掘平台.
- 统一文献检索,实体识别和数据集成,以有效地发现基因与疾病的关系.
主要方法:
- MaBEL集成了来自多个来源的出版物,包括PubMed,Scopus和预印服务器,使用基于DOI的复制.
- 它采用模块化的NLP管道,其中SciSpaCy用于基因/蛋白质识别,BioSyn用于别名规范化,PubTator 3.0用于注释.
- 分布式架构 (Flask,Celery,Docker) 可以实现异步的大规模文本处理.
主要成果:
- 对于七种主要疾病,MaBEL处理了超过14,000个独特的物品.
- 该平台准确地识别了高频率的疾病基因.
- 结果与开放目标平台的关联评分有很强的一致性,验证了疾病与基因关系的发现.
结论:
- 马贝尔提供了一个新的,可扩展的框架,用于先进的生物医学文本挖掘.
- 它促进了快速的假设生成,并加速了转化研究中分子目标的发现.
- 该平台超越了静态的,单个数据库的方法,以进行更全面的文献分析.
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