
Current algorithmic studies of genome rearrangement ignore the length of reversals (or inversions); rather, they only count their number. We introduce a new cost model in which the lengths of the reversed sequences play a role, allowing more flexibility in accounting for mutation phenomena. Our focus is on sorting unsigned (unoriented) permutations by reversals; since this problem remains difficult (NP-hard) in our new model, the best we can hope for are approximation results. We propose an efficient, novel algorithm that takes (a monotonic function f of) length into account as an optimization criterion and study its properties. Our results include an upper bound of O(fn lg2n) for any additive cost measure f on the cost of sorting any n-element permutation, and a guaranteed approximation ratio of O(lg2n) times optimal for sorting a given permutation. Our work poses some interesting questions to both biologists and computer scientists and suggests some new bioinformatic insights that are currently being studied.
genome rearrangements, Chromosome Mapping, Computational Biology, length sensitive cost, Evolution, Molecular, Animals, Humans, Crossing Over, Genetic, sorting by reversal, Algorithms
genome rearrangements, Chromosome Mapping, Computational Biology, length sensitive cost, Evolution, Molecular, Animals, Humans, Crossing Over, Genetic, sorting by reversal, Algorithms
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