NegSPQ:基于基因组数据负表示的类似患者查询
IEEE transactions on computational biology and bioinformatics
|August 14, 2025
概括
这项研究引入了五种新的算法,用于在类似的患者查询 (SPQ) 中进行保护隐私的基因组数据分析. 这些方法利用负信息表示 (NRI) 来保护敏感的基因组序列,同时实现高效的相似性比较.
科学领域:
- 生物信息学是一种生物信息学.
- 基因组数据隐私 基因组数据隐私
- 计算生物学 计算生物学
背景情况:
- 基因组数据越来越多地用于医学和研究.
- 基因组数据是高度敏感的,需要强大的隐私保护.
- 目前用于类似患者查询 (SPQ) 的方法面临隐私挑战.
研究的目的:
- 在SPQ中开发用于基因组数据分析的隐私保护算法.
- 提高基因组序列比较的安全性和效率.
- 为解决保护个人隐私在基因组数据利用中的关键问题.
主要方法:
- 提出了基于负信息表示 (NRI) 的五种算法 (NDB-ED,NDB-Band,NDB-Block,NDB-SIS,NDB-SDS).
- 为了隐私,将基因组序列转换为负数据库 (NDB).
- 在NDB草图上使用编辑距离近似值 (带式和块式) 和设置操作 (SIS,SDS) 来进行不相似性评估.
主要成果:
- 提出的算法证明了有希望的准确性和效率.
- 与现有方法相比,准确度至少提高了10%.
- 减少查询时间至少700倍,显著提高效率.
结论:
- 开发的基于NRI的算法有效地保护SPQ期间的基因组数据隐私.
- 这些算法在准确性和查询速度方面都有显著的改进.
- 这项工作为在敏感应用中利用基因组数据提供了安全有效的框架.
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