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Problems Related to Subsequences and Supersequences
, 1999
"... We present an algorithm for building the automaton that searches for all nonoverlapping occurrences of each subsequence from the set of subsequences. Further, we define Directed Acyclic Supersequence Graph and use it to solve the generalized Shortest Common Supersequence problem, the Longest Common ..."
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Cited by 1 (0 self)
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We present an algorithm for building the automaton that searches for all nonoverlapping occurrences of each subsequence from the set of subsequences. Further, we define Directed Acyclic Supersequence Graph and use it to solve the generalized Shortest Common Supersequence problem, the Longest
Longest Consistent Supersequence problem.
"... Problems related to subsequences and supersequences£ We present an algorithm for building the automaton that searches for all nonoverlapping occurrences of each subsequence from the set of subsequences. Further, we define Directed Acyclic Supersequence Graph and use it to solve the generalized Shor ..."
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Problems related to subsequences and supersequences£ We present an algorithm for building the automaton that searches for all nonoverlapping occurrences of each subsequence from the set of subsequences. Further, we define Directed Acyclic Supersequence Graph and use it to solve the generalized
Maximal Common Subsequences and Minimal Common Supersequences
, 1995
"... The problems of finding a longest common subsequence and a shortest common supersequence of a set of strings are wellknown. They can be solved in polynomial time for two strings (in fact the problems are dual in this case), or for any fixed number of strings, by dynamic programming. ..."
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Cited by 5 (2 self)
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The problems of finding a longest common subsequence and a shortest common supersequence of a set of strings are wellknown. They can be solved in polynomial time for two strings (in fact the problems are dual in this case), or for any fixed number of strings, by dynamic programming.
Searching for Shortest Common Supersequences
, 1996
"... The Shortest Common Supersequence (SCS) problem is a classical problem from stringology which has applications e.g. in Arti cial Intelligence (speci cally planning), mechanical engineering and data compression. The SCS problem is NPcomplete under various restrictions concerning the alphabet si ..."
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Cited by 3 (0 self)
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The Shortest Common Supersequence (SCS) problem is a classical problem from stringology which has applications e.g. in Arti cial Intelligence (speci cally planning), mechanical engineering and data compression. The SCS problem is NPcomplete under various restrictions concerning the alphabet
The ant colony optimization metaheuristic
 in New Ideas in Optimization
, 1999
"... Ant algorithms are multiagent systems in which the behavior of each single agent, called artificial ant or ant for short in the following, is inspired by the behavior of real ants. Ant algorithms are one of the most successful examples of swarm intelligent systems [3], and have been applied to many ..."
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Cited by 385 (23 self)
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to many types of problems, ranging from the classical traveling salesman
On the Parameterized Complexity of the fixed Alphabet Shortest Common Supersequence and Longest Common Subsequence Problems
, 2003
"... INTRODUCTION The Shortest Common Supersequence (SCS) and the Longest Common Subsequence (LCS) are classical problems in computer science. Shortest Common Supersequence (SCS) integer . is a supersequence Longest Common Subsequence (LCS) integer . is a subsequence The LCS and (not so m ..."
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Cited by 45 (0 self)
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INTRODUCTION The Shortest Common Supersequence (SCS) and the Longest Common Subsequence (LCS) are classical problems in computer science. Shortest Common Supersequence (SCS) integer . is a supersequence Longest Common Subsequence (LCS) integer . is a subsequence The LCS and (not so
NonSupersequence, Shortest Common NonSubsequence, and Longest Minimal Common
, 1994
"... On finding minimal, maximal, and consistent sequences ..."
On the complexity of multiple sequence alignment
 J. Comp. Biol
, 1994
"... We study the computational complexity oftwo popular problems in multiple sequence alignment: multiple alignment with SPscore and multiple tree alignment. It is shown that the rst problem is NPcomplete and the second is MAX SNPhard. The complexity of tree alignment with a given phylogeny is also c ..."
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Cited by 326 (13 self)
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considered. Key words: multiple sequence alignment, evolutionary tree, SPscore, computational complexity, approximation algorithm. 1 Introduction. Multiple sequence alignment is one of the most important and challenging problems in computational biology [16, 17]. It plays an essential role in two related
Ten Etudes On Shortest Common Nonsubsequence And Supersequence Approximations
, 1993
"... In this paper we consider polynomialtime approximations for the shortest common nonsubsequence problem and the shortest common supersequence problem: Given a finite language represented by a list of words, find a shortest word, which is not a subsequence or which is a supersequence of every word ..."
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Cited by 1 (0 self)
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In this paper we consider polynomialtime approximations for the shortest common nonsubsequence problem and the shortest common supersequence problem: Given a finite language represented by a list of words, find a shortest word, which is not a subsequence or which is a supersequence of every
Results 1  10
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771