Pattern Discovery in Biomolecular Data: Tools, Techniques, and Applications by Jason T. L. WangPattern Discovery in Biomolecular Data: Tools, Techniques, and Applications by Jason T. L. Wang

Pattern Discovery in Biomolecular Data: Tools, Techniques, and Applications

EditorJason T. L. Wang, Bruce A. Shapiro, Dennis Shasha

Hardcover | March 1, 1999

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Finding patterns in biomolecular data, particularly in DNA and RNA, is at the center of modern biological research. These data are complex and growing rapidly, so the search for patterns requires increasingly sophisticated computer methods. Pattern Discovery in Biomolecular Data provides aclear, up-to-date summary of the principal techniques. Each chapter is self-contained, and the techniques are drawn from many fields, including graph theory, information theory, statistics, genetic algorithms, computer visualization, and vision. Since pattern searches often benefit from multipleapproaches, the book presents methods in their purest form so that readers can best choose the method or combination that fits their needs. The chapters focus on finding patterns in DNA, RNA, and protein sequences, finding patterns in 2D and 3D structures, and choosing system components. This volumewill be invaluable for all workers in genomics and genetic analysis, and others whose research requires biocomputing.
Jason T. L. Wang is at New Jersey Institute of Technology. Bruce A. Shapiro is at National Cancer Institute.
Title:Pattern Discovery in Biomolecular Data: Tools, Techniques, and ApplicationsFormat:HardcoverDimensions:272 pages, 9.09 × 6.1 × 0.91 inPublished:March 1, 1999Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0195119401

ISBN - 13:9780195119404

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Table of Contents

ContributorsIntroductionPart I. Finding Patterns in Sequences1. Aleksandar Milosavljevic: Discovering Patterns in DNA Sequences by the Algorithmic Significance Method2. Jorja G. Henikoff: Assembling Blocks3. Timothy L. Bailey et al.: MEME, MAST, and Meta-MEME: New Tools for Motif Discovery in Protein Sequences4. Jason T. L. Wang et al.: Pattern Discovery and Classification in BiosequencesPart II. Finding Patterns in 3D Structures5. Janice Glasgow, Evan Steeg, and Suzanne Fortier: Motif Discovery in Protein Structure Databases6. Kentaro Tomii and Minoru Kanehisa: Systematic Detection of Protein Structural Motifs7. Isidore Rigoutsos et al.: Representation and Matching of Small Flexible Molecules in Large Databases of 3D Molecular InformationPart III. System Components for Discovery8. Bin Li, Dennis Shasha, and Jason T. L. Wang: A Framework for Biological Pattern Discovery on Networks of Workstations9. Diane J. Cook, Lawrence B. Holder, and Gehad Galal: Discovering Concepts in Structural Data10. David P. Yee et al.: Overview: A System for Tracking and Managing the Results from Sequence Comparison Programs11. Bruce A. Shapiro et al.: RNA Structure Analysis: A Multifaceted ApproachGlossaryReferencesIndex

From Our Editors

Offering a clear and current summation of the principal techniques in finding patterns in biomolecular data, Pattern Discovery in Biomolecular Data: Tools, Techniques, AMD Applications helps biological researchers learn about the increasingly sophisticated methods at their disposal in this rapidly growing field. Jason Wang makes certain to include all of the methods used for pattern searching, particularly with DNA and RNA, so that readers who specialize in genomics and genetic analysis, as well as those whose research includes biocomputing, will have the clearest explanations of the principal techniques at hand.