Investigating the complexity of the double distance problems

March 07, 2023 Β· Declared Dead Β· πŸ› Algorithms for Molecular Biology

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Authors Marilia D. V. Braga, Leonie R. Brockmann, Katharina Klerx, Jens Stoye arXiv ID 2303.04205 Category cs.DS: Data Structures & Algorithms Citations 3 Venue Algorithms for Molecular Biology Last Checked 4 months ago
Abstract
Two genomes over the same set of gene families form a canonical pair when each of them has exactly one gene from each family. Different distances of canonical genomes can be derived from a structure called breakpoint graph, which represents the relation between the two given genomes as a collection of cycles of even length and paths. Then, the breakpoint distance is equal to n - (c_2 + p_0/2), where n is the number of genes, c_2 is the number of cycles of length 2 and p_0 is the number of paths of length 0. Similarly, when the considered rearrangements are those modeled by the double-cut-and-join (DCJ) operation, the rearrangement distance is n - (c + p_e/2), where c is the total number of cycles and p_e is the total number of even paths. The distance formulation is a basic unit for several other combinatorial problems related to genome evolution and ancestral reconstruction, such as median or double distance. Interestingly, both median and double distance problems can be solved in polynomial time for the breakpoint distance, while they are NP-hard for the rearrangement distance. One way of exploring the complexity space between these two extremes is to consider the Οƒ_k distance, defined to be n - [c_2 + c_4 + ... + c_k + (p_0 + p_2 + ... +p_k)/2], and increasingly investigate the complexities of median and double distance for the Οƒ_4 distance, then the Οƒ_6 distance, and so on. While for the median much effort was done in our and in other research groups but no progress was obtained even for the Οƒ_4 distance, for solving the double distance under Οƒ_4 and Οƒ_6 distances we could devise linear time algorithms, which we present here.
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