![A tabu search algorithm for maximum parsimony phylogeny inference [An article from: European Journal of Operational Research]](https://www.ebooknetworking.net/books/B00/0PA/bigB000PAUWEO.jpg)
A tabu search algorithm for maximum parsimony phylogeny inference [An article from: European Journal of Operational Research]
Book Details
Author(s)Y.M. Lin, S.C. Fang, J.L. Thorne
PublisherElsevier
ISBN / ASINB000PAUWEO
ISBN-13978B000PAUWE2
AvailabilityAvailable for download now
Sales Rank99,999,999
MarketplaceUnited States 🇺🇸
Description
This digital document is a journal article from European Journal of Operational Research, published by Elsevier in 2007. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
Phylogeny reconstruction is too complex a combinatorial problem for an exhaustive search, because the number of possible solutions increases exponentially with the number of taxa involved. In this paper, we adopt the parsimony principle and design a tabu search algorithm for finding a most parsimonious phylogeny tree. A special array structure is employed to represent the topology of trees and to generate the neighboring trees. We test the proposed tabu search algorithm on randomly selected data sets obtained from nuclear ribosomal DNA sequence data. The experiments show that our algorithm explores fewer trees to reach the optimal one than the commonly used program ''dnapenny'' (branch-and-bound based) while it generates much more accurate results than the default options of the program ''dnapars'' (heuristic search based). The percentage of search space needed to find the best solution for our algorithm decreased rapidly as the number of taxa increased. For a 20-taxon phylogeny problem, it needs on average to examine only 3.92x10^-^1^5% of the sample space.
Description:
Phylogeny reconstruction is too complex a combinatorial problem for an exhaustive search, because the number of possible solutions increases exponentially with the number of taxa involved. In this paper, we adopt the parsimony principle and design a tabu search algorithm for finding a most parsimonious phylogeny tree. A special array structure is employed to represent the topology of trees and to generate the neighboring trees. We test the proposed tabu search algorithm on randomly selected data sets obtained from nuclear ribosomal DNA sequence data. The experiments show that our algorithm explores fewer trees to reach the optimal one than the commonly used program ''dnapenny'' (branch-and-bound based) while it generates much more accurate results than the default options of the program ''dnapars'' (heuristic search based). The percentage of search space needed to find the best solution for our algorithm decreased rapidly as the number of taxa increased. For a 20-taxon phylogeny problem, it needs on average to examine only 3.92x10^-^1^5% of the sample space.
