一个开源的多语义注释数据集和病毒致癌因素的自动识别工具
Honglian Huang1,2, Danqi Huang1, Ziyi Wei1
1Department of Bioinformatics, School of Life Sciences and Technology, Tongji University, 1239 Siping Road, Shanghai, 200092, China.
Database : the journal of biological databases and curation
|September 25, 2025
概括
这项研究创建了来自八种致癌病毒的病毒致癌因子的大型数据集. 本资源有助于了解癌症的发展,并确定预防和治疗的关键因素.
科学领域:
- 在瘤学瘤学.
- 病毒学 病毒学
- 生物信息学是一种生物信息学.
背景情况:
- 了解致癌病毒对于癌症预防和疫苗开发至关重要.
- 病毒致癌机制涉及遗传变异,生活方式和环境因素.
研究的目的:
- 使用NLP和专家知识构建病毒致癌因素的综合体.
- 分析转录组数据,了解免疫微环境和基因表达.
- 为研究人员和临床医生提供可访问的工具和数据.
主要方法:
- 从551,715个摘要中开发了一个大规模的,含义丰富的病毒致癌因子库.
- 利用自然语言处理 (NLP) 和专家知识进行实体识别.
- 收集和分析转录组数据,包括差异基因表达和免疫微环境分析.
- 创建了一个语义过器来增强实体识别.
主要成果:
- 编制了一个数据集,包含了5,821,308个与病毒致癌相关的实体.
- 通过数据分析,确定了影响病毒致癌的关键因素.
- 建立了一个视觉知识平台和一个开源数据集,供公众访问.
结论:
- 这项研究为病毒致癌机制提供了新的见解.
- 开发的资源有助于快速识别研究和临床线索.
- 这项工作支持早期预防和控制与病毒有关的癌症.
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