## Reconstructing weighted phylogenetic trees and phylogenetic networks using answer set programmingÇakmak, Duygu (2010)
Official URL: http://192.168.1.20/record=b1302884 (Table of Contents) ## AbstractEvolutionary relationships between species can be modeled as a tree (called a phylogeny) whose nodes represent the species, internal vertices represent their ancestors and edges represent genetic relationships. If there are borrowings between species, then a small number of edges that denote such borrowings can be added to phylogenies turning them into (phylogenetic) networks. However, there are too many such trees/networks for a given family of species but no phylogenetic system to automatically analyze them. This thesis fulfills this need in phylogenetics, by introducing novel computational methods and tools for computing weighted phylogenies/networks, using Answer Set Programming (ASP). The main idea is to define a weight function for phylogenies/networks that characterizes their plausibility, and to reconstruct phylogenies/networks whose weights are over a given threshold using ASP solvers. We have studied computational problems related to reconstructing weighted phylogenies/networks based on the compatibility criterion, analyzed their computational complexity, and introduced two sorts of ASP-based methods (representation-based and search-based) for computing weighted phylogenies/networks. Utilizing these methods, we have introduced a novel divide-and-conquer algorithm for computing large weighted phylogenies, and implemented a phylogenetic system (Phylo-ASP) based on it. We have also implemented a phylogenetic system (PhyloNet-ASP) for reconstructing weighted networks. We have shown the applicability and the effectiveness of our methods by performing experiments on two real datasets: Indo European languages, and Quercus species in Turkey. Moreover, we have extended our methods to computing weighted solutions in ASP and modified an ASP solver accordingly, providing a useful tool (CLASP-W) for various ASP applications.
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