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Bioinformatics Algorithms: Techniques and Applications



Bioinformatics Algorithms: Techniques and Applications

Ion Mandoiu, Alexander Zelikovsky

ISBN: 978-0-470-25342-7 February 2008 520 Pages

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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.

Preface ix

Contributors xi

1 Educating Biologists in the 21st Century: Bioinformatics Scientists versus Bioinformatics Technicians 1
Pavel Pevzner

Part I Techniques 7

2 Dynamic Programming Algorithms for Biological Sequence and Structure Comparison 9
Yuzhen Ye and Haixu Tang

3 Graph Theoretical Approaches to Delineate Dynamics of Biological Processes 29
Teresa M. Przytycka and Elena Zotenko

4 Advances in Hidden Markov Models for Sequence Annotation 55
Broňa Brejová, Daniel G. Brown, and Tomáš Vinař

5 Sorting- and FFT-Based Techniques in the Discovery of Biopatterns 93
Sudha Balla, Sanguthevar Rajasekaran, and Jaime Davila

6 A Survey of Seeding for Sequence Alignment 117
Daniel G. Brown

7 The Comparison of Phylogenetic Networks: Algorithms and Complexity 143
Paola Bonizzoni, Gianluca Della Vedova, Riccardo Dondi, and Giancarlo Mauri

Part II Genome and Sequence Analysis 175

8 Formal Models of Gene Clusters 177
Anne Bergeron, Cedric Chauve, and Yannick Gingras

9 Integer Linear Programming Techniques for Discovering Approximate Gene Clusters 203
Sven Rahmann and Gunnar W. Klau

10 Efficient Combinatorial Algorithms for DNA Sequence Processing 223
Bhaskar DasGupta and Ming-Yang Kao

11 Algorithms for Multiplex PCR Primer Set Selection with Amplification Length Constraints 241
K.M. Konwar, I.I. Măndoiu, A.C. Russell, and A.A. Shvartsman

12 Recent Developments in Alignment and Motif Finding for Sequences and Networks 259
Sing-Hoi Sze

Part III Microarray Design and Data Analysis 277

13 Algorithms for Oligonucleotide Microarray Layout 279
Sérgio A. De Carvalho Jr. and Sven Rahmann

14 Classification Accuracy Based Microarray Missing Value Imputation 303
Yi Shi, Zhipeng Cai, and Guohui Lin

15 Meta-Analysis of Microarray Data 329
Saumyadipta Pyne, Steve Skiena, and Bruce Futcher

Part IV Genetic Variation Analysis 353

16 Phasing Genotypes Using a Hidden Markov Model 355
P. Rastas, M. Koivisto, H. Mannila, and E. Ukkonen

17 Analytical and Algorithmic Methods for Haplotype Frequency Inference: What Do They Tell Us? 373
Steven Hecht Orzack, Daniel Gusfield, Lakshman Subrahmanyan, Laurent Essioux, and Sebastien Lissarrague

18 Optimization Methods for Genotype Data Analysis in Epidemiological Studies 395
Dumitru Brinza, Jingwu He, and Alexander Zelikovsky

Part V Structural and Systems Biology 417

19 Topological Indices in Combinatorial Chemistry 419
Sergey Bereg

20 Efficient Algorithms for Structural Recall in Databases 439
Hao Wang, Patra Volarath, and Robert W. Harrison

21 Computational Approaches to Predict Protein–Protein and Domain–Domain Interactions 465
Raja Jothi and Teresa M. Przytycka

Index 493

"This clear and approachable presentation makes the book appropriate for researchers, practioners, and graduate students." (Mathematical Reviews, Issue 2009b)

"This volume will be a nice addition to the bioinformatician's bookshelf." (Quarterly Review of Biology, December 2008)