The problem of reconstructing a string from its error-prone copies, the trace reconstruction problem, was introduced by Vladimir Levenshtein two decades ago. While there has been considerable theoretical work on trace reconstruction, practical solutions have only recently started to emerge in the context of two rapidly developing research areas: immunogenomics and DNA data storage. In immunogenomics, traces correspond to mutated copies of genes, with mutations generated naturally by the adaptive immune system. In DNA data storage, traces correspond to noisy copies of DNA molecules that encode digital data, with errors being artifacts of the data retrieval process. In this paper, we introduce several new trace generation models and open questions relevant to trace reconstruction for immunogenomics and DNA data storage, survey theoretical results on trace reconstruction, and highlight their connections to computational biology. Throughout, we discuss the applicability and shortcomings of known solutions and suggest future research directions.
翻译:20年前,弗拉基米尔·莱文什丁提出了从易出错的拷贝中重建一条绳子的问题,即追踪重建问题。虽然在追踪重建方面进行了大量的理论工作,但最近才开始在两个迅速发展的研究领域(免疫基因组学和DNA数据储存)中出现实际解决办法。在免疫基因组学中,痕迹相当于基因变异的复制件,而基因变异是由适应性免疫系统自然产生的。在DNA数据储存中,痕迹相当于将数字数据编码为编码的DNA分子的响亮复制件,错误是数据检索过程的文物。在本论文中,我们引入了几个新的追踪生成模型和开放问题,以追踪免疫基因组和DNA数据储存的重建,调查关于追踪重建的理论结果,并突出其与计算生物学的联系。我们讨论了已知解决办法的适用性和缺点,并提出未来的研究方向。