
arXiv: 2402.01942
Genome rearrangement is a common model for molecular evolution. In this paper, we consider the Pairwise Rearrangement problem, which takes as input two genomes and asks for the number of minimum-length sequences of permissible operations transforming the first genome into the second. In the Single Cut-and-Join model (Bergeron, Medvedev, & Stoye, J. Comput. Biol. 2010), Pairwise Rearrangement is $\#\textsf{P}$-complete (Bailey, et. al., COCOON 2023), which implies that exact sampling is intractable. In order to cope with this intractability, we investigate the parameterized complexity of this problem. We exhibit a fixed-parameter tractable algorithm with respect to the number of components in the adjacency graph that are not cycles of length $2$ or paths of length $1$. As a consequence, we obtain that Pairwise Rearrangement in the Single Cut-and-Join model is fixed-parameter tractable by distance. Our results suggest that the number of nontrivial components in the adjacency graph serves as the key obstacle for efficient sampling.
Full version of paper that appeared in SWAT 2024; arXiv admin note: text overlap with arXiv:2305.01851
Genomics (q-bio.GN), FOS: Computer and information sciences, Computational Complexity, Genome Rearrangement, 004, Phylogenetics, 92-08, 92D10, 92D20, 68Q17, FOS: Biological sciences, Computer Science - Data Structures and Algorithms, FOS: Mathematics, Mathematics - Combinatorics, Quantitative Biology - Genomics, Data Structures and Algorithms (cs.DS), Combinatorics (math.CO), F.2.2, Single Cut-and-Join, ddc: ddc:004
Genomics (q-bio.GN), FOS: Computer and information sciences, Computational Complexity, Genome Rearrangement, 004, Phylogenetics, 92-08, 92D10, 92D20, 68Q17, FOS: Biological sciences, Computer Science - Data Structures and Algorithms, FOS: Mathematics, Mathematics - Combinatorics, Quantitative Biology - Genomics, Data Structures and Algorithms (cs.DS), Combinatorics (math.CO), F.2.2, Single Cut-and-Join, ddc: ddc:004
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
