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Genetics-Research and Issues Ser.: Discrete Optimization for TSP-like Genome Mapping Problems by D. Ronin (2010, Trade Paperback)

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About this product

Product Identifiers

PublisherNOVA Science Publishers, Incorporated

ISBN-101616681705

ISBN-139781616681708

eBay Product ID (ePID)109293981

Product Key Features

Number of Pages62 Pages

Publication NameDiscrete Optimization for Tsp-Like Genome Mapping Problems

LanguageEnglish

Publication Year2010

SubjectLife Sciences / Genetics & Genomics, Genetics, Algebra / General, Optimization

TypeTextbook

AuthorD. Ronin

Subject AreaMathematics, Science, Medical

SeriesGenetics-Research and Issues Ser.

FormatTrade Paperback

Dimensions

Item Weight4.7 Oz

Item Length6.1 in

Item Width9.1 in

Additional Product Features

Intended AudienceScholarly & Professional

LCCN2010-001744

Dewey Edition22

IllustratedYes

Dewey Decimal572.8/633

Table Of ContentGeneral Introduction; Guided Evolution Strategy Algorithm for Classic Tsp as a Basis for Solving the Genetic/Genomic Tsp-Like Problems; Multilocus Genetic Mapping; Multilocus Consensus Genetic Mapping: Formulation, Model & Algorithms; Tsp-Like Problem In Physical Mapping (Pmp); Conclusions; Index.

SynopsisThis 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., This book introduces a discrete optimisation technique in four applications: classic Traveller 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.

LC Classification NumberQH445.2.D57 2010