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Discrete Optimization for TSP-like Genome Mapping Problems.

By: Contributor(s): Material type: TextTextSeries: Genetics - Research and IssuesPublisher: Hauppauge : Nova Science Publishers, Incorporated, 2010Copyright date: ©2010Edition: 1st edDescription: 1 online resource (73 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781616683740
Subject(s): Genre/Form: Additional physical formats: Print version:: Discrete Optimization for TSP-like Genome Mapping ProblemsDDC classification:
  • 572.8/633
LOC classification:
  • QH445.2 -- .D57 2010eb
Online resources:
Contents:
Intro -- DISCRETE OPTIMIZATION FOR SOME TSP-LIKE GENOME MAPPING PROBLEMS -- DISCRETE OPTIMIZATION FOR SOME TSP-LIKE GENOME MAPPING PROBLEMS -- CONTENTS -- PREFACE -- Chapter 1 GENERAL INTRODUCTION -- Chapter 2 GUIDED EVOLUTION STRATEGY ALGORITHM FOR CLASSIC TSP AS A BASIS FOR SOLVING THE GENETIC/GENOMIC TSP-LIKE PROBLEMS -- 2.1. Introduction -- 2.2. The Problem Solving Methodology -- 2.2.1. The Improvement Heuristics -- 2.2.2. Phase 1: A Guided Local Search Metaheuristic for the TSP -- 2.2.3. Phase 2: Attempting Small Mutations -- 2.3. Experimental results -- 2.3.1. The Problem Data and Parameter Setting -- 2.3.2. Analysis of Different Algorithm Configurations -- 2.3.3. Results for Standard TSP Benchmarks -- Chapter 3 MULTILOCUS GENETIC MAPPING -- 3.1. Introduction -- 3.2. Evolution Strategies For Combinatorial Optimization Problems -- 3.3. The Evolution Strategy Algorithm with Multi-Parametric Mutator (ES-MPM) -- 3.4. Guided Evolution Strategies (GES) for MGM -- 3.5. Experiments on MGM Using Simulated Datasets -- 3.6. An Approach to Increase the Map Reliability by Using Verification Process -- Chapter 4 MULTILOCUS CONSENSUS GENETIC MAPPING: FORMULATION, MODEL AND ALGORITHMS -- 4.1. Introduction -- 4.2. Main Idea of the Approach to Solve MCGM -- 4.3. Full Frame (FF) Algorithm for MCGM -- 4.4. Specific Conflicted Frames (SCF) Algorithm for MCGM -- Chapter 5 TSP-LIKE PROBLEM IN PHYSICAL MAPPING (PMP) -- 5.1. Introduction -- 5.1.1. The Model and Problem Formulation -- 5.1.2. Standard Methodology for Solving Physical Mapping Problem -- 5.1.3. An Alternative Approach to Contig Assembly -- 5.2. Reducing PMP to Standard TSP -- 5.2.1. Clustering Algorithm -- 5.2.2. Looking for Linear Topological Structure -- 5.2.3. Multipoint Ordering Using Global Optimization -- 5.2.4. Re-Sampling Verification of the Obtained Solution.
5.2.5. Merging of Sub-Contigs -- Chapter 6 CONCLUSIONS -- ACKNOWLEDGMENT -- APPENDIX. CHOOSING THRESHOLD Q VALUE FOR PRC CALCULATION -- References -- INDEX -- Blank Page.
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Intro -- DISCRETE OPTIMIZATION FOR SOME TSP-LIKE GENOME MAPPING PROBLEMS -- DISCRETE OPTIMIZATION FOR SOME TSP-LIKE GENOME MAPPING PROBLEMS -- CONTENTS -- PREFACE -- Chapter 1 GENERAL INTRODUCTION -- Chapter 2 GUIDED EVOLUTION STRATEGY ALGORITHM FOR CLASSIC TSP AS A BASIS FOR SOLVING THE GENETIC/GENOMIC TSP-LIKE PROBLEMS -- 2.1. Introduction -- 2.2. The Problem Solving Methodology -- 2.2.1. The Improvement Heuristics -- 2.2.2. Phase 1: A Guided Local Search Metaheuristic for the TSP -- 2.2.3. Phase 2: Attempting Small Mutations -- 2.3. Experimental results -- 2.3.1. The Problem Data and Parameter Setting -- 2.3.2. Analysis of Different Algorithm Configurations -- 2.3.3. Results for Standard TSP Benchmarks -- Chapter 3 MULTILOCUS GENETIC MAPPING -- 3.1. Introduction -- 3.2. Evolution Strategies For Combinatorial Optimization Problems -- 3.3. The Evolution Strategy Algorithm with Multi-Parametric Mutator (ES-MPM) -- 3.4. Guided Evolution Strategies (GES) for MGM -- 3.5. Experiments on MGM Using Simulated Datasets -- 3.6. An Approach to Increase the Map Reliability by Using Verification Process -- Chapter 4 MULTILOCUS CONSENSUS GENETIC MAPPING: FORMULATION, MODEL AND ALGORITHMS -- 4.1. Introduction -- 4.2. Main Idea of the Approach to Solve MCGM -- 4.3. Full Frame (FF) Algorithm for MCGM -- 4.4. Specific Conflicted Frames (SCF) Algorithm for MCGM -- Chapter 5 TSP-LIKE PROBLEM IN PHYSICAL MAPPING (PMP) -- 5.1. Introduction -- 5.1.1. The Model and Problem Formulation -- 5.1.2. Standard Methodology for Solving Physical Mapping Problem -- 5.1.3. An Alternative Approach to Contig Assembly -- 5.2. Reducing PMP to Standard TSP -- 5.2.1. Clustering Algorithm -- 5.2.2. Looking for Linear Topological Structure -- 5.2.3. Multipoint Ordering Using Global Optimization -- 5.2.4. Re-Sampling Verification of the Obtained Solution.

5.2.5. Merging of Sub-Contigs -- Chapter 6 CONCLUSIONS -- ACKNOWLEDGMENT -- APPENDIX. CHOOSING THRESHOLD Q VALUE FOR PRC CALCULATION -- References -- INDEX -- Blank Page.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

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