# Configurations and Minority in the String Consensus Problem

• Amihood Amir
• Haim Paryenty
• Liam Roditty
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7608)

## Abstract

The Closest String Problem is defined as follows. Let S be a set of k strings {s 1,…s k }, each of length ℓ, find a string $$\hat{s}$$, such that the maximum Hamming distance of $$\hat{s}$$ from each of the strings is minimized. We denote this distance with d. The string $$\hat{s}$$ is called a consensus string. In this paper we present two main algorithms, the Configuration algorithm with O(k 2k) running time for this problem, and the Minority algorithm.

The problem was introduced by Lanctot, Li, Ma, Wang and Zhang [13]. They showed that the problem is $$\cal{NP}$$-hard and provided an IP approximation algorithm. Since then the closest string problem has been studied extensively. This research can be roughly divided into three categories: Approximate, exact and practical solutions. This paper falls under the exact solutions category. Despite the great effort to obtain efficient algorithms for this problem an algorithm with the natural running time of O(ℓ k) was not known. In this paper we close this gap.

Our result means that algorithms solving the closest string problem in times O(ℓ2), O(ℓ3), O(ℓ4) and O(ℓ5) exist for the cases of k = 2,3,4 and 5, respectively. It is known that, in fact, the cases of k = 2,3, and 4 can be solved in linear time. No efficient algorithm is currently known for the case of k = 5. We prove the minority lemma that exploit surprising properties of the closest string problem and enable constructing the closest string in a sequential fashion. This lemma with some additional ideas give an O(ℓ2) time algorithm for computing a closest string of 5 binary strings.

## Keywords

Close String Binary String Input String Consensus Problem Column Type
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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© Springer-Verlag Berlin Heidelberg 2012

## Authors and Affiliations

• Amihood Amir
• 1
• 2
• Haim Paryenty
• 1
• Liam Roditty
• 1
1. 1.Department of Computer ScienceBar Ilan UniversityRamat GanIsrael
2. 2.Department of Computer ScienceJohns Hopkins UniversityBaltimoreUSA