EPR字典：一种用于单向和双向FM索引中恒定时间搜索的实用快速数据结构
EPR-dictionaries: A practical and fast data structure for constant time searches in unidirectional and bidirectional FM-indices
摘要：
我们介绍了一种新的，实用的方法进行精确的搜索在一个单向和双向FM索引在$O(1)$时间每一步，而使用$O(\log σ* n) + o(\log σ* σ* n)$位的空间。这是通过用一种新的数据结构，即增强前缀秩字典（EPR字典）来替换二进制小波树来完成的。我们在SeqAn C++库中实现了这种方法，并通过实验验证了我们的理论结果。此外，我们比较了我们的实现与其他免费提供的双向索引的实现，并表明我们之间的$\approx 2.6-4.8$倍更快。这将对许多依赖（2）FM索引的实际实现（例如用于读取映射）的生物信息学应用产生很大影响。据我们所知，这是2FM索引中搜索步骤的恒定时间方法的第一个实现。
英文摘要：
We introduce a new, practical method for conducting an exact search in a uni- and bidirectional FM index in $O(1)$ time per step while using $O(\log σ* n) + o(\log σ* σ* n)$ bits of space. This is done by replacing the binary wavelet tree by a new data structure, the Enhanced Prefixsum Rank dictionary (EPR-dictionary). We implemented this method in the SeqAn C++ library and experimentally validated our theoretical results. In addition we compared our implementation with other freely available implementations of bidirectional indices and show that we are between $\approx 2.6-4.8$ times faster. This will have a large impact for many bioinformatics applications that rely on practical implementations of (2)FM indices e.g. for read mapping. To our knowledge this is the first implementation of a constant time method for a search step in 2FM indices.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
