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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Algorithmica 13 (1995), S. 211-243 
    ISSN: 1432-0541
    Keywords: Pattern matching ; Dynamic programming ; Extended regular expressions ; Molecular biology ; Gene recognition
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract Some recognition problems are either too complex or too ambiguous to be expressed as a simple pattern matching problem using a sequence or regular expression pattern. In these cases, a richer environment is needed to describe the “patterns” and recognition techniques used to perform the recognition. Some researchers have turned to artificial-intelligence techniques and multistep matching approaches for the problems of gene recognition [5], [7], [18], protein structure recognition [13], and on-line character recognition [6]. This paper presents a class of problems which involve finding matches to “patterns of patterns,” orsuper- patterns, given solutions to the lower-level patterns. The expressiveness of this problem class rivals that of traditional artificial-intelligence characterizations, and yet polynomial-time algorithms are described for each problem in the class.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Algorithmica 14 (1995), S. 85-121 
    ISSN: 1432-0541
    Keywords: Pattern matching ; Regular expressions ; Concave gap penalties ; Approximate matching
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract Given a sequenceA of lengthM and a regular expressionR of lengthP, an approximate regular expression pattern-matching algorithm computes the score of the optimal alignment betweenA and one of the sequencesB exactly matched byR. An alignment between sequencesA=a1a2 ... aM andB=b1b2... bN is a list of ordered pairs, 〈(i1,j1), (i2j2), ..., (it,jtt)〉 such that ik 〈 ik+1 and jk 〈 jk+1. In this case the alignmentaligns symbols aik and bjk, and leaves blocks of unaligned symbols, orgaps, between them. A scoring schemeS associates costs for each aligned symbol pair and each gap. The alignment's score is the sum of the associated costs, and an optimal alignment is one of minimal score. There are a variety of schemes for scoring alignments. In a concave gap penalty scoring schemeS={δ, w}, a function δ(a, b) gives the score of each aligned pair of symbolsa andb, and aconcave function w(k) gives the score of a gap of lengthk. A function w is concave if and only if it has the property that, for allk 〉 1, w(k + 1) −w(k) ≤w(k) −w(k −1). In this paper we present an O(MP(logM + log2 P)) algorithm for approximate regular expression matching for an arbitraryδ and any concavew.
    Type of Medium: Electronic Resource
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