Temporal phylogenetic networks and logic programming
Theory and Practice of Logic Programming
Seeing the trees and their branches in the network is hard
Theoretical Computer Science
Comparison of Tree-Child Phylogenetic Networks
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Applications of answer set programming in phylogenetic systematics
Logic programming, knowledge representation, and nonmonotonic reasoning
Reconstructing evolution of natural languages: complexity and parameterized algorithms
COCOON'06 Proceedings of the 12th annual international conference on Computing and Combinatorics
Computing weighted solutions in ASP: representation-based method vs. search-based method
Annals of Mathematics and Artificial Intelligence
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Phylogenies, i.e., evolutionary histories, play a major role in representing the relationships among groups of entities, such as species, genes, and languages. Their pervasiveness has led scientists, mainly biologists, mathematicians, and computer scientists, to develop methods and tools for their accurate reconstruction. Most of these tools, however, assume that the underlying model of speciation is a tree. While a good first approximation, trees fail to model the evolutionary histories in the presence of complex evolutionary events, such as lateral gene transfer and hybrid speciation among biological entities, and borrowing of linguistic features among natural languages. These events lead to “networks”, rather than trees, of relationships. In this dissertation, we present two methodologies for reconstructing phylogenetic networks. In the biological context, our method is based on the observation that contained within the branches of a (species) phylogenetic networks are phylogenetic trees that model the evolution of individual genes. To study the accuracy of our new method, as well as existing methods, we have developed a suite of simulation tools and error measures. Our simulation studies show a clear outperformance of existing methods. In historical linguistics, we extend the Ringe-Warnow model of language evolution, to incorporate non-treelike evolutionary events; our new methodology is called “perfect phylogenetic networks”. We have implemented a reconstruction method, based on the new methodology, and analyzed a dataset of Indo-European languages.