Cover image for Metaheuristics for String Problems in Bio-informatics

Metaheuristics for String Problems in Bio-informatics

Author Paola Festa , Christian Blum
Release Date: 2016/08/01
ISBN: 9781848218123
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Book Description

So-called string problems are abundant in bioinformatics and computational biology. New optimization problems dealing with DNA or protein sequences are constantly arising and researchers are highly in need of efficient optimization techniques for solving them.

One obstacle for optimization practitioners is the atypical nature of these problems which require an interdisciplinary approach in order to solve them efficiently and accurately.

Table of Contents

  1. Cover
  2. Dedication
  3. Title
  4. Copyright
  5. Preface
  6. Acknowledgments
  7. List of Acronyms
  8. 1 Introduction
    1. 1.1. Complete methods for combinatorial optimization
    2. 1.2. Approximate methods: metaheuristics
    3. 1.3. Outline of the book
  9. 2 Minimum Common String Partition Problem
    1. 2.1. The MCSP problem
    2. 2.2. An ILP model for the UMCSP problem
    3. 2.3. Greedy approach
    4. 2.4. Construct, merge, solve and adapt
    5. 2.5. Experimental evaluation
    6. 2.6. Future work
  10. 3 Longest Common Subsequence Problems
    1. 3.1. Introduction
    2. 3.2. Algorithms for the LCS problem
    3. 3.3. Algorithms for the RFLCS problem
    4. 3.4. Future work
  11. 4 The Most Strings With Few Bad Columns Problem
    1. 4.1. The MSFBC problem
    2. 4.2. An ILP model for the MSFBC problem
    3. 4.3. Heuristic approaches
    4. 4.4. ILP-based large neighborhood search
    5. 4.5. Experimental evaluation
    6. 4.6. Future work
  12. 5 Consensus String Problems
    1. 5.1. Introduction
    2. 5.2. Organization of this chapter
    3. 5.3. The closest string problem and the close to most string problem
    4. 5.4. The farthest string problem and the far from most string problem
    5. 5.5. An ILP-based heuristic
    6. 5.6. Future work
  13. 6 Alignment Problems
    1. 6.1. Introduction
    2. 6.2. The pairwise alignment problem
    3. 6.3. The multiple alignment problem
    4. 6.4. Conclusion and future work
  14. 7 Conclusions
    1. 7.1. DNA sequencing
    2. 7.2. Founder sequence reconstruction
    3. 7.3. Final remarks
  15. Bibliography
  16. Index
  17. End User License Agreement
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