Handbook of Computational Molecular Biology  book cover
1st Edition

Handbook of Computational Molecular Biology

Edited By

Srinivas Aluru

ISBN 9781584884064
Published December 21, 2005 by Chapman and Hall/CRC
1104 Pages 354 B/W Illustrations

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Book Description

The enormous complexity of biological systems at the molecular level must be answered with powerful computational methods. Computational biology is a young field, but has seen rapid growth and advancement over the past few decades. Surveying the progress made in this multidisciplinary field, the Handbook of Computational Molecular Biology offers comprehensive, systematic coverage of the various techniques and methodologies currently available.

Accomplished researcher Srinivas Aluru leads a team of experts from around the world to produce this groundbreaking, authoritative reference. With discussions ranging from fundamental concepts to practical applications, this book details the algorithms necessary to solve novel problems and manage the massive amounts of data housed in biological databases throughout the world. Divided into eight sections for convenient searching, the handbook covers methods and algorithms for sequence alignment, string data structures, sequence assembly and clustering, genome-scale computational methods in comparative genomics, evolutionary and phylogenetic trees, microarrays and gene expression analysis, computational methods in structural biology, and bioinformatics databases and data mining.

The Handbook of Computational Molecular Biology is the first resource to integrate coverage of the broad spectrum of topics in computational biology and bioinformatics. It supplies a quick-reference guide for easy implementation and provides a strong foundation for future discoveries in the field.

Table of Contents

Sequence Alignments
Pairwise Sequence Alignments; Benjamin N. Jackson and Srinivas Aluru
Spliced Alignment and Similarity-Based Gene Recognition; Alexey D. Neverov, Andrey A. Mironov, and Mikhail S. Gelfand
Multiple Sequence Alignment; Osamu Gotoh, Shinsuke Yamada, and Tetsushi Yada
Parametric Sequence Alignment; David Fernández-Baca and Balaji Venkatachalam
String Data Structures
Lookup Tables, Suffix Trees and Suffix Arrays; Srinivas Aluru
Suffix Tree Applications in Computational Biology; Pang Ko and Srinivas Aluru
Enhanced Suffix Arrays and Applications; Mohamed I. Abouelhoda, Stefan Kurtz, and Enno Ohlebusch
Genome Assembly and EST Clustering
Computational Methods for Genome Assembly; Xiaoqiu Huang
Assembling the Human Genome; Richa Agarwala
Comparative Methods for Sequence Assembly; Vamsi Veeramachaneni
Information Theoretic Approach to Genome Reconstruction; Suchendra Bhandarkar, Jinling Huang, and Jonathan Arnold
Expressed Sequence Tags: Clustering and Applications; Anantharaman Kalyanaraman and Srinivas Aluru
Algorithms for Large-Scale Clustering and Assembly of Biological Sequence Data; Scott J. Emrich, Anantharaman Kalyanaraman, and Srinivas Aluru
Genome-Scale Computational Methods
Comparisons of Long Genomic Sequences: Algorithms and Applications; Michael Brudno and Inna Dubchak
Chaining Algorithms and Applications in Comparative Genomics; Enno Ohlebusch and Mohamed I. Abouelhoda
Computational Analysis of Alternative Splicing; Mikhail S. Gelfand
Human Genetic Linkage Analysis; Alejandro A. Schäffer
Combinatorial Methods for Haplotype Inference; Dan Gusfield and Steven Hecht Orzack
An Overview of Phylogeny Reconstruction; C. Randal Linder and Tandy Warnow
Consensus Trees and Supertrees; Oliver Eulenstein
Large-Scale Phylogenetic Analysis; Tandy Warnow
High-Performance Phylogeny Reconstruction; David A. Bader and Mi Yan
Microarrays and Gene Expression Analysis
Microarray Data: Annotation, Storage, Retrieval and Communication; Catherine A. Ball and Gavin Sherlock
Computational Methods for Microarray Design; Hui-Hsien Chou
Clustering Algorithms for Gene Expression Analysis; Pierre Baldi, G. Wesley Hatfield, and Li M. Fu
Biclustering Algorithms: A Survey; Amos Tanay, Roded Sharan, and Ron Shamir
Identifying Gene Regulatory Networks from Gene Expression Data; Vladimir Filkov
Modeling and Analysis of Gene Networks Using Feedback Control Theory; Hana El Samad and Mustafa Khammash
Computational Structural Biology
Predicting Protein Secondary and Supersecondary Structure; Mona Singh
Protein Structure Prediction with Lattice Models; William E. Hart and Alantha Newman
Protein Structure Determination via NMR Spectral Data; Guohui Lin, Xin Tu, and Xiang Wan
Geometric Processing of Reconstructed 3D Maps of Molecular Complexes; Chandrajit Bajaj and Zeyun Yu
In Search of Remote Homolog; Dong Xu, Ognen Duzlevski, and Xiu-Feng Wan
Biomolecular Modeling using Parallel Supercomputers; Laxmikant V. Kalé, Klaus Schulten, Robert D. Skeel, Glenn Martyna, Mark Tuckerman, James C. Phillips, Sameer Kumar, and Gengbin Zheng
Bioinformatic Databases and Data Mining
String Search in External Memory: Data Structures and Algorithms; Paolo Ferragina
Index Structures for Approximate Matching in Sequence Databases; Tamer Kahveci and Ambuj K. Singh
Algorithms for Motif Search; Sanguthevar Rajasekaran
Data Mining in Computational Biology; Mohammed J. Zaki and Karlton Sequeira

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“The material is well organized  and documented, with good presentation and special care on typography. It is highly recommended for any researcher or graduate student interested in an insight into computational biology deeper than the practical use as “black boxes” of computer programs or web servers.”
—Arturo Rojo-Dominguez, in Bulletin of Mathematical Biology, (2007) 69: 2775-2776

“It is to the credit of the author and publisher that they have been able to put together such a complete and well organized handbook this early. …Useful to the researcher looking for either an introduction to the field in general or go learn about areas outside his particular area of expertise.”

"...valuable to those new to the field as well as more experienced researchers.  The handbook has done a good job of developing major areas in the field while maintaining a well-organized structure.  The 'Handbook for Computational Molecular Biology' will be a great resource to those interested in this exciting field."                                                     - Suzanne Sindi, Bioinformatics, Feb., 2007, Vol. 38, No. 3