Bioinformatics Algorithms: Techniques and Applications targets the future collaboration of researchers in algorithms, bioinformatics, and molecular biology. It addresses critical bioinformatics research areas of protein-protein interaction, molecular modeling in drug design, and structural biology.

Preface ix Contributors xi 1 Educating Biologists in the 21st Century: Bioinformatics Scientists versus Bioinformatics Technicians 1Pavel Pevzner Part I Techniques 7 2 Dynamic Programming Algorithms for Biological Sequence and Structure Comparison 9Yuzhen Ye and Haixu Tang 3 Graph Theoretical Approaches to Delineate Dynamics of Biological Processes 29Teresa M. Przytycka and Elena Zotenko 4 Advances in Hidden Markov Models for Sequence Annotation 55Broňa Brejová, Daniel G. Brown, and Tomáš Vinař 5 Sorting- and FFT-Based Techniques in the Discovery of Biopatterns 93Sudha Balla, Sanguthevar Rajasekaran, and Jaime Davila 6 A Survey of Seeding for Sequence Alignment 117Daniel G. Brown 7 The Comparison of Phylogenetic Networks: Algorithms and Complexity 143Paola Bonizzoni, Gianluca Della Vedova, Riccardo Dondi, and Giancarlo Mauri Part II Genome and Sequence Analysis 175 8 Formal Models of Gene Clusters 177Anne Bergeron, Cedric Chauve, and Yannick Gingras 9 Integer Linear Programming Techniques for Discovering Approximate Gene Clusters 203Sven Rahmann and Gunnar W. Klau 10 Efficient Combinatorial Algorithms for DNA Sequence Processing 223Bhaskar DasGupta and Ming-Yang Kao 11 Algorithms for Multiplex PCR Primer Set Selection with Amplification Length Constraints 241K.M. Konwar, I.I. Măndoiu, A.C. Russell, and A.A. Shvartsman 12 Recent Developments in Alignment and Motif Finding for Sequences and Networks 259Sing-Hoi Sze Part III Microarray Design and Data Analysis 277 13 Algorithms for Oligonucleotide Microarray Layout 279Sérgio A. De Carvalho Jr. and Sven Rahmann 14 Classification Accuracy Based Microarray Missing Value Imputation 303Yi Shi, Zhipeng Cai, and Guohui Lin 15 Meta-Analysis of Microarray Data 329Saumyadipta Pyne, Steve Skiena, and Bruce Futcher Part IV Genetic Variation Analysis 353 16 Phasing Genotypes Using a Hidden Markov Model 355P. Rastas, M. Koivisto, H. Mannila, and E. Ukkonen 17 Analytical and Algorithmic Methods for Haplotype Frequency Inference: What Do They Tell Us? 373Steven Hecht Orzack, Daniel Gusfield, Lakshman Subrahmanyan, Laurent Essioux, and Sebastien Lissarrague 18 Optimization Methods for Genotype Data Analysis in Epidemiological Studies 395Dumitru Brinza, Jingwu He, and Alexander Zelikovsky Part V Structural and Systems Biology 417 19 Topological Indices in Combinatorial Chemistry 419Sergey Bereg 20 Efficient Algorithms for Structural Recall in Databases 439Hao Wang, Patra Volarath, and Robert W. Harrison 21 Computational Approaches to Predict Protein–Protein and Domain–Domain Interactions 465Raja Jothi and Teresa M. Przytycka Index 493

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. Ion I. M?Andoiu, PhD, is Assistant Professor in the Computer Science and Engineering Department at the University of Connecticut. His research focuses on the design and analysis of exact and approximation algorithms for NP-hard optimization problems, particularly in the areas of bioinfor-matics and computational molecular biology, VLSI computer-aided design and manufacturing, and ad-hoc wireless networks.