miCDER:用于联合miRNA-疾病实体和多层次监管关系提取的上下文感知变压器模型
Jiangcheng Shi1, Lijun Wang2, Lixue Liu2
1School of Life Sciences, Tiangong University, Tianjin, 300387, China. shijiangcheng@tiangong.edu.cn.
BMC genomics
|November 28, 2025
概括
研究人员开发了miCDER,这是一个基于变压器的新型模型,用于提取microRNA疾病调节相互作用. 该工具通过从生物医学文献中识别新的关联,显著提高了对疾病机制的理解.
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
- 基因组学就是基因组学.
背景情况:
- 微RNA (miRNA) 失调与各种人类疾病有关.
- 现有的方法与标准化,细粒度的miRNA-疾病相互作用数据和多层次的监管分析扎.
研究的目的:
- 开发一个可靠的模型来提取详细的miRNA-疾病调节相互作用.
- 构建一个全面的miRNA-疾病关系的知识图.
主要方法:
- 构建一个细粒度,多层次的注释生物医学数据集.
- 开发miCDER,一个基于变压器的模型,用于联合实体和关系提取.
- 使用上下文编码和跨跨变压器的注意力.
主要成果:
- miCDER实现了最先进的性能:NER F1=87.34%,RE F1=77.28%,表现优于SpERT.等基线.
- 在CoNLL04和ADE数据集上证明了可通用性,分别具有竞争力和优异的结果.
- 提取了93,221个调控三重体,构建了MAAD-HCD-KG,包括1,735个新的目标关系.
结论:
- 该miCDER模型有效地从生物医学文本中提取细粒度的监管信息.
- 所生成的MAAD-HCD-KG知识图表促进了对miRNA相关疾病的研究.
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