An improved approximation algorithm for the complementary maximal strip recovery problem

  • Authors:

  • Zhong Li;Randy Goebel;Lusheng Wang;Guohui Lin

  • Affiliations:

  • Department of Computing Science, University of Alberta, Alberta, Canada;Department of Computing Science, University of Alberta, Alberta, Canada;Department of Computer Science, City University of Hong Kong, Hong Kong, China;Department of Computing Science, University of Alberta, Alberta, Canada

  • Venue:
  • FAW-AAIM'11 Proceedings of the 5th joint international frontiers in algorithmics, and 7th international conference on Algorithmic aspects in information and management
  • Year:
  • 2011

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Abstract

Given two genomic maps G1 and G2 each represented as a sequence of n gene markers, the maximal strip recovery (MSR) problem is to retain the maximum number of markers in both G1 and G2 such that the resultant subsequences, denoted as G1* and G2*, can be partitioned into the same set of maximal strips, which are common substrings of length greater than or equal to two. The complementary maximal strip recovery (CMSR) problem has the complementary goal to delete the minimum number of markers. Both MSR and CMSR have been shown NP-hard and APX-complete, and they admit a 4-approximation and a 3-approximation respectively. In this paper, we present an improved 7/3 -approximation algorithm for the CMSR problem, with its worst-case performance analysis done through a sequential amortization.