Heuristics. (c2006)

Includes bibliographical references (l. 70).

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Main Author: Kallab, Chadi (author)
Format: masterThesis
Published: 2006
Subjects:
Online Access:http://hdl.handle.net/10725/925
https://doi.org/10.26756/th.2006.54
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author Kallab, Chadi
author_facet Kallab, Chadi
author_role author
dc.creator.none.fl_str_mv Kallab, Chadi
dc.date.none.fl_str_mv 2006
2006-06-16
2011-10-27T07:39:21Z
2011-10-27T07:39:21Z
2011-10-27
dc.identifier.none.fl_str_mv http://hdl.handle.net/10725/925
https://doi.org/10.26756/th.2006.54
dc.language.none.fl_str_mv en
dc.publisher.none.fl_str_mv Lebanese American University
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Heuristic programming
Combinatorial optimization
dc.title.none.fl_str_mv Heuristics. (c2006)
Encoding for parsimony phylogenetic trees & generic implementations
dc.type.none.fl_str_mv Thesis
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/masterThesis
description Includes bibliographical references (l. 70).
eu_rights_str_mv openAccess
format masterThesis
id LAURepo_3f6ef58abb2adb3194e93dabe84bed94
language_invalid_str_mv en
network_acronym_str LAURepo
network_name_str Lebanese American University repository
oai_identifier_str oai:laur.lau.edu.lb:10725/925
publishDate 2006
publisher.none.fl_str_mv Lebanese American University
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
spelling Heuristics. (c2006)Encoding for parsimony phylogenetic trees & generic implementationsKallab, ChadiHeuristic programmingCombinatorial optimizationIncludes bibliographical references (l. 70).This thesis focuses on the NP-Hard problem of finding an optimal tree topology where leaves represent biological sequences. The problem consists of minimizing the number of changes between given and/or derived sequences. As the number of sequences to be compared increases, the size of the search space grows exponentially, requesting the use of optimization methods, to come up with an acceptable optimal topology. Even though, research is relating a large number of species and gene families to each others, the computation intensive load of many popular methods for evaluating trees (ex: parsimony and maximum likelihood) establish the quasi-inexistence of an exact solution for more than about 20 sequences. The alignment of two sequences (pairwise alignment), or multiple sequences (Multiple Sequence Alignment - MSA), and the alignment of short or long sequences such as an entire genome may require different types of algorithms. The algorithms used in all of these four cases are dynamic programming, linear programming based or heuristic-based or a combination of them. For large numbers of sequences to be aligned, heuristic methods may give a result similar to the exact solution offered by the dynamic programming or linear programming based algorithms, but in much shorter time. Heuristics used in phylogenetic inference include greedy algorithms, hill climbing, simulated annealing, and genetic algorithms. Thus, this research aims to suggest a general way to encode the problem into instances of different heuristic algorithms. Another focus of the document would be to suggest that the heuristics used, be implemented in a most optimal way, trying to get a compromise between speedup, flexibility and detailed tracing/chronology of each run of the algorithms.1 bound copy: vii, 70 leaves; ill., tables; 30 cm. available at RNL.Lebanese American University2011-10-27T07:39:21Z2011-10-27T07:39:21Z20062011-10-272006-06-16Thesisinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesishttp://hdl.handle.net/10725/925https://doi.org/10.26756/th.2006.54eninfo:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/9252020-05-18T14:53:50Z
spellingShingle Heuristics. (c2006)
Kallab, Chadi
Heuristic programming
Combinatorial optimization
status_str publishedVersion
title Heuristics. (c2006)
title_full Heuristics. (c2006)
title_fullStr Heuristics. (c2006)
title_full_unstemmed Heuristics. (c2006)
title_short Heuristics. (c2006)
title_sort Heuristics. (c2006)
topic Heuristic programming
Combinatorial optimization
url http://hdl.handle.net/10725/925
https://doi.org/10.26756/th.2006.54