Discrete optimization for TSP-like genome mapping problems

D. Mester; D. Ronin; M. Korostishevsky; M. Frenkel; A. Korol; Z. Bräysy; O. Dullaert; W. Raa

Discrete optimization for TSP-like genome mapping problems

D. Mester, D. Ronin, M. Korostishevsky, M. Frenkel, A. Korol, Z. Bräysy, O. Dullaert, W. Raa

Department of Evolutionary and Environmental Biology

Research output: Book/Report › Book › peer-review

Abstract

This book introduces a discrete optimization technique in four applications: classic Traveler Salesperson Problem (TSP), Multilocus Genetic Mapping, Multilocus Consensus Genetic Mapping, and Physical Mapping. Each of the four sections contains the problem formulation, description of the algorithm, and experimental results. The foregoing problems are solved on the basis of Guided Evolution Strategy (GES) algorithm. The algorithm was implemented in MultiPoint package (http://multiqtl.com). The developed analytical tools were applied in many genome mapping projects.

Original language	English
Publisher	Nova Science Publishers, Inc.
Number of pages	63
ISBN (Print)	9781616681708
State	Published - Feb 2011

ASJC Scopus subject areas

General Physics and Astronomy

Cite this

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AU - Ronin, D.

AU - Korostishevsky, M.

AU - Frenkel, M.

AU - Korol, A.

AU - Bräysy, Z.

AU - Dullaert, O.

AU - Raa, W.

PY - 2011/2

Y1 - 2011/2

N2 - This book introduces a discrete optimization technique in four applications: classic Traveler Salesperson Problem (TSP), Multilocus Genetic Mapping, Multilocus Consensus Genetic Mapping, and Physical Mapping. Each of the four sections contains the problem formulation, description of the algorithm, and experimental results. The foregoing problems are solved on the basis of Guided Evolution Strategy (GES) algorithm. The algorithm was implemented in MultiPoint package (http://multiqtl.com). The developed analytical tools were applied in many genome mapping projects.

AB - This book introduces a discrete optimization technique in four applications: classic Traveler Salesperson Problem (TSP), Multilocus Genetic Mapping, Multilocus Consensus Genetic Mapping, and Physical Mapping. Each of the four sections contains the problem formulation, description of the algorithm, and experimental results. The foregoing problems are solved on the basis of Guided Evolution Strategy (GES) algorithm. The algorithm was implemented in MultiPoint package (http://multiqtl.com). The developed analytical tools were applied in many genome mapping projects.

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BT - Discrete optimization for TSP-like genome mapping problems

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Discrete optimization for TSP-like genome mapping problems

Abstract

ASJC Scopus subject areas

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