// Workers AI · dad joke modeWhat did the generalized suffix tree say? "I'm rooted in knowledge

In computer science, a generalized suffix tree is a suffix tree for a set of strings. Given the set of strings $D=S_{1},S_{2},\dots ,S_{d}$ of total length $n$ , it is a Patricia tree containing all $n$ suffixes of the strings. It is mostly used in bioinformatics.^[1]

Functionality

It can be built in $\Theta (n)$ time and space, and can be used to find all $z$ occurrences of a string $P$ of length $m$ in $O(m+z)$ time, which is asymptotically optimal (assuming the size of the alphabet is constant^[2]^: 119).

When constructing such a tree, each string should be padded with a unique out-of-alphabet marker symbol (or string) to ensure no suffix is a substring of another, guaranteeing each suffix is represented by a unique leaf node.

Algorithms for constructing a GST include Ukkonen's algorithm (1995) and McCreight's algorithm (1976).

Example

A suffix tree for the strings ABAB and BABA is shown in a figure above. They are padded with the unique terminator strings $0 and $1. The numbers in the leaf nodes are string number and starting position. Notice how a left to right traversal of the leaf nodes corresponds to the sorted order of the suffixes. The terminators might be strings or unique single symbols. Edges on $ from the root are left out in this example.

Alternatives

An alternative to building a generalized suffix tree is to concatenate the strings, and build a regular suffix tree or suffix array for the resulting string. When hits are evaluated after a search, global positions are mapped into documents and local positions with some algorithm and/or data structure, such as a binary search in the starting/ending positions of the documents.

References

↑ Paul Bieganski; John Riedl; John Carlis; Ernest F. Retzel (1994). "Generalized Suffix Trees for Biological Sequence Data". Biotechnology Computing, Proceedings of the Twenty-Seventh Hawaii International Conference on. pp. 35–44. doi:10.1109/HICSS.1994.323593.
↑ Gusfield, Dan (1999) [1997]. Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology. USA: Cambridge University Press. ISBN 978-0-521-58519-4.

External links

Media related to Generalized suffix tree at Wikimedia Commons
A C implementation of Generalized Suffix Tree for two strings

[BRCR-1] Paul Bieganski; John Riedl; John Carlis; Ernest F. Retzel (1994). "Generalized Suffix Trees for Biological Sequence Data". Biotechnology Computing, Proceedings of the Twenty-Seventh Hawaii International Conference on. pp. 35–44. doi:10.1109/HICSS.1994.323593.

[Gus97-2] Gusfield, Dan (1999) [1997]. Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology. USA: Cambridge University Press. ISBN 978-0-521-58519-4.

[1]

[2]

v t e Strings
String metric	Approximate string matching Bitap algorithm Damerau–Levenshtein distance Edit distance Gestalt pattern matching Hamming distance Jaro–Winkler distance Lee distance Levenshtein automaton Levenshtein distance Wagner–Fischer algorithm
String-searching algorithm	Apostolico–Giancarlo algorithm Boyer–Moore string-search algorithm Boyer–Moore–Horspool algorithm Knuth–Morris–Pratt algorithm Rabin–Karp algorithm Raita algorithm Trigram search Two-way string-matching algorithm Zhu–Takaoka string matching algorithm
Multiple string searching	Aho–Corasick Commentz-Walter algorithm
Regular expression	Comparison of regular-expression engines Regular grammar Thompson's construction Nondeterministic finite automaton
Sequence alignment	BLAST Hirschberg's algorithm Needleman–Wunsch algorithm Smith–Waterman algorithm
Data structure	DAFSA Substring index Suffix array Suffix automaton Suffix tree Compressed suffix array LCP array FM-index Generalized suffix tree Rope Ternary search tree Trie
Other	Parsing Pattern matching Compressed pattern matching Longest common subsequence Longest common substring Sequential pattern mining Sorting String rewriting systems String operations

This page was redesigned at the edge.

A page that knows where it met you.