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A Space and Time Efficient Algorithm for Constructing Compressed Suffix Arrays

机译:一种高效的时空压缩后缀数组构造算法

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With the first human DNA being decoded into a sequence of about 2.8 billion characters, much biological research has been centered on analyzing this sequence. Theoretically speaking, it is now feasible to accommodate an index for human DNA in the main memory so that any pattern can be located efficiently. This is due to the recent breakthrough on compressed suffix arrays, which reduces the space requirement from O(n log n) bits to O(n) bits. However, constructing compressed suffix arrays is still not an easy task because we still have to compute suffix arrays first and need a working memory of O(n log n) bits (i.e., more than 13 gigabytes for human DNA). This paper initiates the study of constructing compressed suffix arrays directly from the text. The main contribution is a construction algorithm that uses only O(n) bits of working memory, and the time complexity is O(n log n). Our construction algorithm is also time and space efficient for texts with large alphabets such as Chinese or Japanese. Precisely, when the alphabet size is |Σ|, the working space is O(n log|Σ|) bits, and the time complexity remains O(n log n), which is independent of |Σ|.
机译:随着第一个人类DNA被解码为约28亿个字符的序列,许多生物学研究都集中在分析该序列上。从理论上讲,现在可以在主内存中容纳人类DNA的索引,以便可以有效地定位任何模式。这是由于最近对压缩后缀数组的突破,将空间需求从O(n log n)位减少到O(n)位。但是,构造压缩后缀数组仍然不是一件容易的事,因为我们仍然必须首先计算后缀数组,并且需要O(n log n)位(即,人类DNA超过13 GB)的工作存储器。本文直接从文本开始研究构建压缩后缀数组。主要贡献是一种仅使用工作内存的O(n)位的构造算法,时间复杂度为O(n log n)。对于具有大字母的文本(例如中文或日语),我们的构造算法在时间和空间上也很有效。精确地,当字母大小为|Σ|时,工作空间为O(n log |Σ|)位,时间复杂度保持为O(n log n),与|Σ|无关。

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