在使用双向光束搜索系统的DNA存储系统中高效的痕迹重建
Zhenhao Gu1,2, Hongyi Xin3, Puru Sharma1
1Department of Computer Science, School of Computing, National University of Singapore, Singapore 117417, Singapore.
iScience
|November 24, 2025
概括
我们开发了一种新的DNA数据存储算法,可以更快,更准确地重建序列. 这种双向光束搜索 (BBS) 方法提高了DNA数据存储的效率和可靠性.
科学领域:
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
- 数据存储数据存储数据存储
背景情况:
- DNA 数据存储是一个快速增长的领域,需要高效的解码算法.
- 目前用于痕迹重建的方法通常使用对齐或读取校正,这些方法在速度和通用性上有局限性.
- 这些现有方法在复杂的数据集和固定的错误率假设方面扎.
研究的目的:
- 开发一种新,高效和准确的算法,用于DNA数据存储中的痕迹重建.
- 通过引入概率方法来解决现有方法的局限性.
- 为了提高从杂的DNA序列解码数据的速度和可靠性.
主要方法:
- 使用k-th级马尔科夫链模型进行痕迹重建的概率公式.
- 确定马尔科夫链最可能生成的共识序列.
- 开发用于线性时间共识重建的双向光束搜索 (BBS) 算法.
主要成果:
- 双向光束搜索 (BBS) 算法在线时间内重建共识序列.
- 在多个公开的纳米孔测序数据集上,BBS实现了最高级别的准确性.
- BBS比现有的痕迹重建方法快大约20倍.
结论:
- 建议的概率方法和BBS算法显著提高了DNA数据存储效率.
- BBS为解码噪音DNA测序读取提供了更具通用性和更快的解决方案.
- 这项工作有可能推动DNA数据存储系统的实际应用.
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