Polynomial supertree methods in phylogenomics : algorithms simulations and software One of the objectives in modern biology especially phylogenetics is to build larger clades of the Tree of Life. Large scale phylogenetic analysis involves several serious challenges. The aim of this thesis is to contribute to some of the open problems in this context. In computational phylogenetics supertree methods provide a way to reconstruct larger clades of the Tree of Life. We present a novel polynomial time approach for the computation of supertrees called FlipCut supertree. Our method combines the computation of minimum cuts from graph based methods with a matrix representation method namely Minimum Flip Supertrees. Here the input trees are encoded in a 0 1  matrix. We present a heuristic to search for a minimum set of 0 1 flips such that the resulting matrix admits a directed perfect phylogeny. In contrast to other polynomial time approaches our results can be interpreted in the sense that we try to minimize a global objective function namely the number of flips in the input matrix. We extend our approach by using edge weights to weight the columns of the 0 1  matrix. In order to compare our new FlipCut supertree method with other recent polynomial supertree methods and matrix representation methods we present a large scale simulation study using two different data sets. Our findings illustrate the trade off between accuracy and running time in supertree construction as well as the pros and cons of different supertree approaches. Furthermore we present EPoS a modular software framework for phylogenetic analysis and visualization. It fills the gap between command line based algorithmic packages and visual tools without sufficient support for computational methods. By combining a powerful graphical user interface with a plugin system that allows simple integration of new algorithms visualizations and data structures we created a framework that is easy to use to extend and that covers all important steps of a phylogenetic analysis.