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Radiation Hybrid Map Construction Problem Parameterized

  • Chihao Zhang
  • Haitao Jiang
  • Binhai Zhu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7402)

Abstract

In this paper, we study the Radiation Hybrid Map Construction (RHMC) problem which is about reconstructing a genome from a set of gene clusters. The problem is known to be NP-complete even when all gene clusters are of size two and the corresponding problem (RHMC 2) admits efficient constant-factor approximation algorithms. In this paper, for the first time, we consider the more general case when the gene clusters can have size either two or three (RHMC 3). Let pRHMC be a parameterized version of RHMC where the parameter is the size of solution. We present a linear kernel for pRHMC 3 of size 22k, together with a bounded search tree algorithm, we obtain an FPT algorithm running in O(6 k k + n) time. For pRHMC 2 we present a bounded search tree algorithm which runs in O *(2.45 k ) time, greatly improving the previous bound using weak kernels.

Keywords

Radiation Hybrid Linear Kernel Good Pattern Free Cluster Search Tree Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Chihao Zhang
    • 1
  • Haitao Jiang
    • 2
  • Binhai Zhu
    • 3
  1. 1.Department of Computer ScienceShanghai Jiao Tong UniversityShanghaiChina
  2. 2.School of Computer Science and TechnologyShandong UniversityJinanChina
  3. 3.Department of Computer ScienceMontana State UniversityBozemanUSA

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