Optimización multiobjetivo en mallas variables (MOVMO) aplicada a la interferencia de árboles filogenéticos.

One of the most relevant problems in Bioinformatics and Computational Biology is the search and reconstruction of the most accurate phylogenetic tree that explains, more exactly possible, the evolutionary relationships among species from a given dataset. Different criteria have been employed to evaluate the accuracy of evolutionary hypothesis in order to guide a search algorithm towards the best tree. However, these criteria may lead to distinct phylogenies, which are often conflicting among them. Therefore, a multiobjective approach can be useful. In this work, we present a phylogenetic adaptation of the algorithm multiobjective optimization based variable meshes (MOVMO) for inferring phylogenies, with finality to tackle the phylogenetic inference problem according to two optimality criteria: maximum parsimony and maximum likelihood. The aim of this approach is to propose a complementary view of phylogenetics according to the maximum parsimony and maximum likelihood criteria, in order to generate a set of trade-off phylogenetic topologies that represent a consensus between both optimality criteria. Experiments on four real nucleotide datasets show that our proposal can achieve promising results, under both multiobjective and biological approachs, with regard to other classical and recent multiobjective metaheuristics from the state-of-the-art.

• Үндсэн зохиолч: Hidalgo Reyes, Carlos Alfredo (author)
• Формат: bachelorThesis
• Хэл сонгох: spa
• Хэвлэсэн: 2017
• Нөхцлүүд: Inferencia Filogenética; Computación Evolutiva; Optimización Multiobjetivo; Bioinformática; Biología Computaciona
• Онлайн хандалт: http://repositorio.uteq.edu.ec/handle/43000/2176