Titlebook: Algorithms for Computational Biology; 5th International Co Jesper Jansson,Carlos Martín-Vide,Miguel A. Vega-R Conference proceedings 2018 S

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Fixed Parameter Algorithms and Hardness of Approximation Results for the Structural Target Controllaced and analyzed, both on randomly generated networks, and on bio-medical ones. In this paper, we show that the Structural Target Controllability problem is fixed parameter tractable when parameterized by the number of target nodes. We also prove that the problem is hard to approximate at a factor b

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https://doi.org/10.1007/978-3-531-90394-1riant, called ., aims at inferring a species tree based on a model of speciation and duplication where duplications are clustered in duplication episodes. The goal is to minimize the number of such episodes. The second variant, ., aims at inferring a species . based on a model of speciation and reti

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https://doi.org/10.1007/978-3-642-91319-8ransforms one into another. When we use permutations to represent the genomes, this reduces to the problem of sorting a permutation using some sequence of rearrangements. The traditional approach is to find a sequence of minimum length. However, some studies show that some rearrangements are more li

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Verknüpfungen geben dem Text einen Sinnays to do this is to consider the size of the smallest sequence of rearrangement events required to transform one genome into another, characterizing the rearrangement distance problem. Computationally, genomes can be represented as permutations of integers and, with this, the problem can be reduced