Exploring New Search Algorithms and Hardware for Phylogenetics: RAxML Meets the IBM Cell

Phylogenetic inference is considered to be one of the grand challenges in Bioinformatics due to the immense computational requirements. RAxML is currently among the fastest and most accurate programs for phylogenetic tree inference under the Maximum Likelihood (ML) criterion. First, we introduce new tree search heuristics that accelerate RAxML by a factor of 2.43 while returning equally good trees. The performance of the new search algorithm has been assessed on 18 real-world datasets comprising 148 up to 4,843 DNA sequences. We then present the implementation, optimization, and evaluation of RAxML on the IBM Cell Broadband Engine. We address the problems and provide solutions pertaining to the optimization of floating point code, control flow, communication, and scheduling of multi-level parallelism on the Cel

Inference of Many-Taxon Phylogenies

Phylogenetic trees are tree topologies that represent the evolutionary history of a set of organisms. In this thesis, we address computational challenges related to the analysis of large-scale datasets with Maximum Likelihood based phylogenetic inference. We have approached this using different strategies: reduction of memory requirements, reduction of running time, and reduction of man-hours

Mathematical Problems in Molecular Evolution and Next Generation Sequencing

The focus of this work is the development of new mathematical methods for problems in phylogenetic tree inferences. In the first part we solve several problems related to so-called partitioned alignments. In the second part we demonstrate how to calculate all identical subtrees of a given labeled tree. We make use of this to implement an efficient method for avoiding redundant likelihood operations during phylogenetic tree inferences