Bioinformatics Algorithms: Techniques and Applications

Bioinformatics Algorithms: Techniques and Applications

Editor(s): Ion I. Mǎndoiu, Alexander Zelikovsky

Published Online: 9 AUG 2007

Print ISBN: 9780470097731

Online ISBN: 9780470253441

DOI: 10.1002/9780470253441

About this Book

Presents algorithmic techniques for solving problems in bioinformatics, including applications that shed new light on molecular biology

This book introduces algorithmic techniques in bioinformatics, emphasizing their application to solving novel problems in post-genomic molecular biology. Beginning with a thought-provoking discussion on the role of algorithms in twenty-first-century bioinformatics education, Bioinformatics Algorithms covers:

  • General algorithmic techniques, including dynamic programming, graph-theoretical methods, hidden Markov models, the fast Fourier transform, seeding, and approximation algorithms

  • Algorithms and tools for genome and sequence analysis, including formal and approximate models for gene clusters, advanced algorithms for non-overlapping local alignments and genome tilings, multiplex PCR primer set selection, and sequence/network motif finding

  • Microarray design and analysis, including algorithms for microarray physical design, missing value imputation, and meta-analysis of gene expression data

  • Algorithmic issues arising in the analysis of genetic variation across human population, including computational inference of haplotypes from genotype data and disease association search in case/control epidemiologic studies

  • Algorithmic approaches in structural and systems biology, including topological and structural classification in biochemistry, and prediction of protein-protein and domain-domain interactions

Each chapter begins with a self-contained introduction to a computational problem; continues with a brief review of the existing literature on the subject and an in-depth description of recent algorithmic and methodological developments; and concludes with a brief experimental study and a discussion of open research challenges. This clear and approachable presentation makes the book appropriate for researchers, practitioners, and graduate students alike.

Table of contents

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    2. Chapter 7

      The Comparison of Phylogenetic Networks: Algorithms and Complexity (pages 143–173)

      Paola Bonizzoni, Gianluca Della Vedova, Riccardo Dondi and Giancarlo Mauri

    3. Chapter 8

      Formal Models of Gene Clusters (pages 175–202)

      Anne Bergeron, Cedric Chauve and Yannick Gingras

    4. Chapter 15

      Meta-Analysis of Microarray Data (pages 329–352)

      Saumyadipta Pyne, Steve Skiena and Bruce Futcher

    5. Chapter 17

      Analytical and Algorithmic Methods for Haplotype Frequency Inference: What do they Tell Us? (pages 373–394)

      Steven Hecht Orzack, Daniel Gusfield, Lakshman Subrahmanyan, Laurent Essioux and Sebastien Lissarrague

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    7. You have free access to this content

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