• Journal of KIISE:Computer Systems and Theory
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• v.32 no.6
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• pp.268-278
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• 2005

We consider constructing the generalized suffix way of strings A and B when the suffix arrays of A and B are given, j.e., merging two suffix arrays of A and B. There are efficient algorithms to merge some special suffix arrays such as the odd array and the even array. However, for the general case that A and B are arbitrary strings, no efficient merging algorithms have been developed. Thus, one had to construct the generalized suffix arrays of A and B by constructing the suffix array of A$\#$B$\$$ from scratch, even though the suffix ways of A and B are given. In this paper, we Present efficient merging algorithms for the suffix arrays of two arbitrary strings A and B drawn from constant and integer alphabets. The experimental results show that merging two suffix ways of A and B are about 5 times faster than constructing the suffix way of A$\#$B$\$$ from scratch for constant alphabets. Our algorithms include searching all suffixes of string B in the suffix array of A. To do this, we use suffix links in suffix ways and we developed efficient algorithms for computing the suffix links. Efficient computation of suffix links is another contribution of this paper because it can be used to solve other problems occurred in bioinformatics that should search all suffixes of a given string in the suffix array of another string such as computing matching statistics, finding longest common substrings, and so on. The experimental results show that our methods for computing suffix links is about 3-4 times faster than the previous fastest methods.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.8
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• pp.319-326
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• 2007

To perform fast searching in massive data such as DNA strings, the most efficient method is to construct full-text index data structures of given strings. The widely used full-text index structures are suffix trees and suffix arrays. Since the suffix may uses less space than the suffix tree, the suffix array is proper for DNA strings. Previously developed construction algorithms of suffix arrays are not suitable for DNA strings since those are designed for integer alphabets. We propose a fast algorithm to construct suffix arrays on DNA strings whose alphabet sizes are fixed by 4. We reduce the construction time by improving encoding and merging steps on Kim et al.[1]'s algorithm. Experimental results show that our algorithm constructs suffix arrays on DNA strings 1.3-1.6 times faster than Kim et al.'s algorithm, and also for other algorithms in most cases.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04a
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• pp.973-975
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• 2004

대표적인 인덱스 자료 구조인 써픽스 트리와 써픽스 배열은 긴 문자열에서 임의의 패턴을 검색하는 데 효율적이다. 써픽스 트리는 써픽스 배열보다 큰공간을 차지하지만, 이미 구축된 써픽스 트리의 정보를 이용하여 쉽게 합병할 수 있다. 본 논문에서는 문자열 A와 B에 대한 써픽스 배열이 구축되어 있을 때 A#B$의 일반화된 써픽스 배열을 구축하기 위한 합병 알고리즘을 두 가지 제시하였다. 이 알고리즘을 사용하면 기존의 유전체 서열 써픽스 배열을 재사용하는 방식으로 합병하여, 빠른 시간 안에 효율적으로 합병된 써픽스 배열을 만들 수 있다. 실험 결과, 합병 알고리즘은 일반화된 써픽스 배열을 다시 구축하는 것보다 5배정도 빠른 속도를 보였다.