1st Edition

Handbook of Computational Molecular Biology

Edited By Srinivas Aluru Copyright 2006
    1108 Pages 354 B/W Illustrations
    by Chapman & Hall

    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.

    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
    Phylogenetics
    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
    Index

    Biography

    Srinivas Aluru

    “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.”
    —Books-On-Line

    "...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