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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Algorithmica 13 (1995), S. 106-134 
    ISSN: 1432-0541
    Keywords: Sequence comparison ; Local alignment ; Dynamic programming ; Candidate-list paradigm ; Linear-space algorithm
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract This paper presents practical algorithms for building an alignment of two long sequences from a collection of “alignment fragments,” such as all occurrences of identical 5-tuples in each of two DNA sequences. We first combine a time-efficient algorithm developed by Galil and coworkers with a space-saving approach of Hirschberg to obtain a local alignment algorithm that uses0((M+N+F logN) logM) time and0(M+N) space to align sequences of lengthsM andN from a pool of F alignment fragments. Ideas of Huang and Miller are then employed to develop a time- and space-efficient algorithm that computesn best nonintersecting alignments for anyn〉1. An example illustrates the utility of these methods.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Bulletin of mathematical biology 55 (1993), S. 503-524 
    ISSN: 1522-9602
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Mathematics
    Notes: Abstract This paper presents a dynamic programming algorithm for aligning two sequeces when the alignment is constrained to lie between two arbitrary boundary lines in the dynamic programming matrix. For affine gap penalties, the algorithm requires onlyO(F) computation time andO(M+N) space, whereF is the area of the feasible region andM andN are the sequence lengths. The result extends to concave gap penalties, with somewhat increased time and space bounds.
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    Springer
    Journal of combinatorial optimization 3 (1999), S. 199-211 
    ISSN: 1573-2886
    Keywords: computational biology ; ultrametric trees ; approximation algorithms ; branch-and-bound
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract An edge-weighted tree is called ultrametric if the distances from the root to all the leaves in the tree are equal. For an n by n distance matrix M, the minimum ultrametric tree for M is an ultrametric tree T = (V, E, w) with leaf set {1,..., n} such that dT(i, j) ≥ M[i, j] for all i, j and $$\sum {_{e \in E} w(e)}$$ is minimum, where dT(i, j) is the distance between i and j on T. Constructing minimum ultrametric trees from distance matrices is an important problem in computational biology. In this paper, we examine its computational complexity and approximability. When the distances satisfy the triangle inequality, we show that the minimum ultrametric tree problem can be approximated in polynomial time with error ratio 1.5(1 + ⌈log n⌉), where n is the number of species. We also develop an efficient branch-and-bound algorithm for constructing the minimum ultrametric tree for both metric and non-metric inputs. The experimental results show that it can find an optimal solution for 25 species within reasonable time, while, to the best of our knowledge, there is no report of algorithms solving the problem even for 12 species.
    Type of Medium: Electronic Resource
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  • 4
    Book
    Book
    Boca Raton, FL [u.a.] :Chapman & Hall/CRC,
    Title: Spanning trees and optimization problems /
    Author: Wu, Bang Ye
    Contributer: Chao, Kun-Mao
    Publisher: Boca Raton, FL [u.a.] :Chapman & Hall/CRC,
    Year of publication: 2004
    Pages: XV, 184 S.
    Series Statement: Discrete mathematics and its applications
    ISBN: 1-584-88436-3
    Type of Medium: Book
    Language: English
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