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The first is that the question is still open and there is still work to do to achieve a complete and relevant method for representing and analyzing phylogeny. For this purpose, combinatorial networks have a great potential and have already started to build the foundations of next-generation phylogenomics.   On the other hand, the presentation has indirectly shown how recent advancements in sequence analysis and NGS altered the way we look at evolution, henceforth the reconstruction of the evolution. The more we discover about the molecular biology of DNA and recombination events, the more constraints and variability arises when it comes to formalize them into mathematically exploitable objects.   We have to not only take into account biological relevancy, relevance,  but also the complexity of the algorithms. Though NGS have radically improved our understanding of evolution, it has also caused the soaring of the  available amount of data, and it is crucial to keep in mind that speed matters as much as precision and efficiency to be able to exploit all the available information in a reasonable amount of time. Besides, other methods have been proposed, for example \cite{Smith_Brown_Hinchliff_2013} introduced methods for aligning, synthesizing and analyzing rooted phylogenetic trees.