1,475 research outputs found
Tree Contractions and Evolutionary Trees
An evolutionary tree is a rooted tree where each internal vertex has at least
two children and where the leaves are labeled with distinct symbols
representing species. Evolutionary trees are useful for modeling the
evolutionary history of species. An agreement subtree of two evolutionary trees
is an evolutionary tree which is also a topological subtree of the two given
trees. We give an algorithm to determine the largest possible number of leaves
in any agreement subtree of two trees T_1 and T_2 with n leaves each. If the
maximum degree d of these trees is bounded by a constant, the time complexity
is O(n log^2(n)) and is within a log(n) factor of optimal. For general d, this
algorithm runs in O(n d^2 log(d) log^2(n)) time or alternatively in O(n d
sqrt(d) log^3(n)) time
Composing Distributed Data-intensive Web Services Using a Flexible Memetic Algorithm
Web Service Composition (WSC) is a particularly promising application of Web
services, where multiple individual services with specific functionalities are
composed to accomplish a more complex task, which must fulfil functional
requirements and optimise Quality of Service (QoS) attributes, simultaneously.
Additionally, large quantities of data, produced by technological advances,
need to be exchanged between services. Data-intensive Web services, which
manipulate and deal with those data, are of great interest to implement
data-intensive processes, such as distributed Data-intensive Web Service
Composition (DWSC). Researchers have proposed Evolutionary Computing (EC)
fully-automated WSC techniques that meet all the above factors. Some of these
works employed Memetic Algorithms (MAs) to enhance the performance of EC
through increasing its exploitation ability of in searching neighbourhood area
of a solution. However, those works are not efficient or effective. This paper
proposes an MA-based approach to solving the problem of distributed DWSC in an
effective and efficient manner. In particular, we develop an MA that hybridises
EC with a flexible local search technique incorporating distance of services.
An evaluation using benchmark datasets is carried out, comparing existing
state-of-the-art methods. Results show that our proposed method has the highest
quality and an acceptable execution time overall.Comment: arXiv admin note: text overlap with arXiv:1901.0556
Exact Asymptotic Results for a Model of Sequence Alignment
Finding analytically the statistics of the longest common subsequence (LCS)
of a pair of random sequences drawn from c alphabets is a challenging problem
in computational evolutionary biology. We present exact asymptotic results for
the distribution of the LCS in a simpler, yet nontrivial, variant of the
original model called the Bernoulli matching (BM) model which reduces to the
original model in the large c limit. We show that in the BM model, for all c,
the distribution of the asymptotic length of the LCS, suitably scaled, is
identical to the Tracy-Widom distribution of the largest eigenvalue of a random
matrix whose entries are drawn from a Gaussian unitary ensemble. In particular,
in the large c limit, this provides an exact expression for the asymptotic
length distribution in the original LCS problem.Comment: 4 pages Revtex, 2 .eps figures include
Bethe Ansatz in the Bernoulli Matching Model of Random Sequence Alignment
For the Bernoulli Matching model of sequence alignment problem we apply the
Bethe ansatz technique via an exact mapping to the 5--vertex model on a square
lattice. Considering the terrace--like representation of the sequence alignment
problem, we reproduce by the Bethe ansatz the results for the averaged length
of the Longest Common Subsequence in Bernoulli approximation. In addition, we
compute the average number of nucleation centers of the terraces.Comment: 14 pages, 5 figures (some points are clarified
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