Abstract
Motivated by comparative genomics, Chen et al. [9] introduced the Maximum Duo-preservation String Mapping (MDSM) problem in which we are given two strings \(s_1\) and \(s_2\) from the same alphabet and the goal is to find a mapping \(\pi \) between them so as to maximize the number of duos preserved. A duo is any two consecutive characters in a string and it is preserved in the mapping if its two consecutive characters in \(s_1\) are mapped to same two consecutive characters in \(s_2\). The MDSM problem is known to be NP-hard and there are approximation algorithms for this problem [3, 5], all of which consider only the “unweighted” version of the problem in the sense that a duo from \(s_1\) is preserved by mapping to any same duo in \(s_2\) regardless of their positions in the respective strings. However, it is well-desired in comparative genomics to find mappings that consider preserving duos that are “closer” to each other under some distance measure [18].
In this paper, we introduce a generalized version of the problem, called the Maximum-Weight Duo-preservation String Mapping (MWDSM) problem, capturing both duos-preservation and duos-distance measures in the sense that mapping a duo from \(s_1\) to each preserved duo in \(s_2\) has a weight, indicating the “closeness” of the two duos. The objective of the MWDSM problem is to find a mapping so as to maximize the total weight of preserved duos. We give a polynomial-time 6-approximation algorithm for this problem.
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Mehrabi, S. (2017). Approximating Weighted Duo-Preservation in Comparative Genomics. In: Cao, Y., Chen, J. (eds) Computing and Combinatorics. COCOON 2017. Lecture Notes in Computer Science(), vol 10392. Springer, Cham. https://doi.org/10.1007/978-3-319-62389-4_33
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