Radiation hybrid map construction problem parameterized

Abstract

In this paper, we study the Radiation hybrid map construction ($\mathsf{{RHMC} }$) problem which is about reconstructing a genome from a set of gene clusters. The problem is known to be $\mathsf{{NP} }$-complete even when all gene clusters are of size two and the corresponding problem ($\mathsf{{RHMC}_2 }$) 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 ($\mathsf{{RHMC}_3 }$). Let ${p\text{- }\mathsf {RHMC} }$ be a parameterized version of $\mathsf{{RHMC} }$ where the parameter is the size of solution. We present a linear kernel for ${p\text{- }\mathsf {RHMC}_3 }$ of size $22k$ that when combined with a bounded search-tree algorithm, gives an FPT algorithm running in $O(6^kk+n)$ time. For ${p\text{- }\mathsf {RHMC}_3 }$ we present a bounded search tree algorithm which runs in $O^*(2.45^k)$ time, greatly improving the previous bound using weak kernels.