Improvevement of Fitch function for Maximum Parsimony in Phylogenetic Reconstruction with Intel AVX2 assembler instructions

The Maximum Parsimony problem aims at reconstructing a phylogenetic tree from DNA, RNA or protein sequences while minimizing the number of evolutionary changes. Much work has been devoted by the Computer Science community to solve this NP-complete problem and many techniques have been used or designed in order to decrease the computation time necessary to obtain an acceptable solution. In this paper we report an improvement of the evaluation of the Fitch function for Maximum Parsimony using AVX2 assembler instruction of Intel (TM) processor

Local Search for the Maximum Parsimony Problem

Four local search algorithms are investigated for the phylogenetic tree reconstruction problem under the Maximum Parsimony criterion. A new subtree swapping neighborhood is introduced and studied in combination with an effective array-based tree representation. Computational results are shown on a set of randomly generated benchmark instances as well as on 8 real problems (sequences of phytopathogen γ-proteobacteria) and compared with two references from the literature

Progressive Tree Neighborhood applied to the Maximum Parsimony Problem

The Maximum Parsimony (MP) problem aims at reconstructing a phylogenetic tree from DNA sequences while minimizing the number of genetic transformations. To solve this NP-complete problem, heuristic methods have been developed, often based on local search. In this paper, we focus on the influence of the neighborhood relations. After analyzing the advantages and drawbacks of the well-known Nearest Neighbor Interchange (NNI), Subtree Pruning Regrafting (SPR), and Tree-Bisection-Reconnection (TBR) neighborhoods, we introduce the concept of Progressive Neighborhood (PN), which consists of constraining progressively the size of the neighborhood as the search advances. We empirically show that applied to the MP problem, this PN turns out to be more efficient and robust than the classic neighborhoods using a descent algorithm. Indeed, it allows us to find better solutions with a smaller number of iterations or trees evaluated

Voisinage d'arbre évolutif appliqué au problème Maximum de Parcimonie

Le problème Maximum Parcimonie vise à reconstruire un arbre phylogénétique à partir de séquences ADN de manières à ce que le nombre de mutations génétiques survenues au cours de l\u27évolution soit minimal. Pour résoudre ce problème NP-complet, de nombreuses méthodes heuristiques ont été développées, pour la plupart basées sur la recherche locale. Ici, nous nous intéressons à l\u27influence de la relation de voisinage utilisée et introduisons le concept de voisinage évolutif. Nous montrons empiriquement que ce voisinage évolutif s\u27avère plus puissant et robuste que les voisinages classiques

Maximum Parsimony Phylogenetic Inference Using Simulated Annealing

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A Bottom-Up Implementation of Path-Relinking for Phylogenetic Reconstruction Applied to Maximum Parsimony

In this article we describe a bottom-up implementation of Path-Relinking for Phylogenetic Trees in the context of the resolution of the Maximum Parsimony problem with Fitch optimality criterion. This bottom-up implementation is compared to two versions of an existing top-down implementation. We show that our implementation is more efficient, more interesting to compare trees and to give an estimation of the distance between two trees in terms of the number of transformation