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Look Inside Integer Linear Programming in Computational and Systems Biology

Integer Linear Programming in Computational and Systems Biology
An Entry-Level Text and Course

£49.99

  • Date Published: June 2019
  • availability: In stock
  • format: Hardback
  • isbn: 9781108421768

£ 49.99
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  • Integer linear programming (ILP) is a versatile modeling and optimization technique that is increasingly used in non-traditional ways in biology, with the potential to transform biological computation. However, few biologists know about it. This how-to and why-do text introduces ILP through the lens of computational and systems biology. It uses in-depth examples from genomics, phylogenetics, RNA, protein folding, network analysis, cancer, ecology, co-evolution, DNA sequencing, sequence analysis, pedigree and sibling inference, haplotyping, and more, to establish the power of ILP. This book aims to teach the logic of modeling and solving problems with ILP, and to teach the practical 'work flow' involved in using ILP in biology. Written for a wide audience, with no biological or computational prerequisites, this book is appropriate for entry-level and advanced courses aimed at biological and computational students, and as a source for specialists. Numerous exercises and accompanying software (in Python and Perl) demonstrate the concepts.

    • Presents the first-of-its-kind introduction to integer linear programming through the lens of computational and systems biology
    • Includes 330 extended examples and exercises which mix logical thinking and practical application
    • Accompanying software requires no previous computer programming knowledge and allows the reader to explore the material and develop skills in modeling and solving ILPs
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    Reviews & endorsements

    'In his classic accessible teaching style, Gusfield teaches us why integer linear programming (ILP) is the most useful mathematical idea you've probably never heard of. Read this book to learn how what you don't know can hurt you, and why ILP should be your new favorite method.' Trey Ideker, University of California, San Diego

    'Once again, Dan Gusfield has written an accessible book that shows that algorithmic rigor need not be sacrificed when solving real-world problems. He explains integer linear programming in the context of real-world biology. In doing so, the reader has an enriched understanding of both algorithmic details and the challenges in modern biology.' Russ Altman, Stanford University, California

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    Product details

    • Date Published: June 2019
    • format: Hardback
    • isbn: 9781108421768
    • length: 428 pages
    • dimensions: 260 x 181 x 27 mm
    • weight: 0.95kg
    • contains: 123 b/w illus.
    • availability: In stock
  • Table of Contents

    Preface
    Part I:
    1. A fly-over introduction
    2. Biological networks and graphs
    3. Character compatibility
    4. Near-cliques
    5. Parsimony in phylogenetics
    6. RNA folding
    7. Protein problems
    8. Tanglegrams
    9. TSP in genomics
    10. Molecular sequence analysis
    11. Metabolic networks and engineering
    12. ILP idioms
    Part II:
    13. Communities and cuts
    14. Corrupted data and extensions in phylogenetics
    15. More tanglegrams and trees
    16. Return to Steiner-trees
    17. Exploiting protein networks
    18. More strings and sequences
    19. Max-likelihood pedigrees
    20. Haplotyping
    21. Extended exercises
    22. What's next?
    Epilogue: opinionated comments.

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    Integer Linear Programming in Computational and Systems Biology

    Dan Gusfield

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  • Author

    Dan Gusfield, University of California, Davis
    Dan Gusfield is Distinguished Professor of Computer Science at the University of California, Davis, and a Fellow of the IEEE, the ACM, and the International Society of Computational Biology (ISCB). His previous books include The Stable Marriage Problem (1989, with Robert W. Irving), Algorithms on Strings, Trees and Sequences (Cambridge, 1997) and ReCombinatorics (2014). He has served as chair of the computer science department at UCD (2000–04), and was the founding Editor-in-Chief of the IEEE/ACM Transactions of Computational Biology and Bioinformatics until January 2009. He has been instrumental in the definition and development of the intersection between computer science and computational biology.

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