Bioinformatics Algorithms: Techniques and Applications

by Ion Mandoiu (Georgia State Univ., USA ); Alexander Zelikovsky (Georgia State Univ., USA )

• ISBN13: 9780470253427
• ISBN10: 0470253428
• Format: eBook
• Copyright: 2008-02-01
• Publisher: Wiley-Interscience

Summary

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.

Table of Contents

Preface

Contributors

Educating Biologists in the 21st century: Bioinformatics Scientists versus Bioinformatics Technicians

Techniques

Dynamic Programming Algorithms for Biological Sequence and Structure Comparison

Graph Theoretical Approaches to Delineate Dynamics of biological Processes

Advances in Hidden Markov Models for Sequence Annotation

Sorting- and FFT-Based Techniques in the Discovery of Biopatterns

A Survey of Seeding for Sequence Alignment

The Comparison of Phylogenetic Networks: Algorithms and complexity

Genome and Sequence Analysis

Formal Models of Gene Clusters

Integer Linear Programming Techniques for Discovering Approximate gene Clusters

Efficient Combinatorial Algorithms for DNA Sequence Processing

Algorithms for Multiplex PCR Primer Set Selection with Amplification Length constraints (K.M. Konwar

Recent Developments in Alignment and Motif Finding for Sequences and Networks

Microarray Design and Data Analysis

Algorithms for Oligonucleotide Microarray Layout

Classification Accuracy Based Microarray Missing Value Imputation

Meta-Analysis of Microarray Data

Genetic Variation Analysis

Phasing Genotypes Using a Hidden Markov Model

Analytical and Algorithmic Methods for Haplotype Frequency Inference: What Do they Tell Us?

Optimization Methods for Genotype Data Analysis in Epidemiological Studies

Structural and Systems Biology

Topological Indices in Combinatorial Chemistry

Efficient Algorithms for Structural Recall in Databases

Computational Approaches to Predict Protein-Protein and Domain-Domain Interactions

Index

Table of Contents provided by Publisher. All Rights Reserved.