
Pattern Discovery in Biomolecular Data
Tools, Techniques, and Applications
Oxford University Press Inc
Published on 2. December 1999
Book
Hardback
272 pages
978-0-19-511940-4 (ISBN)
Description
This book presents, in one convenient volume, the work of researchers in the field of pattern discovery, a fundamental operation used in the process of extracting knowledge from biomolecular data. The significant growth of the size of biomolecular data has lead scientists to place increasing importance on developing novel techniques for this knowledge extraction. With this fact in mind, the editors have compiled this clear, up-to-date summary of the principle techniques of pattern discovery in molecular biology, in the hope that readers will build on these techniques and make discoveries of their own. The techniques are drawn from many fields of mathematical science, including graph theory, information theory, statistics, and computer vision.
Because there are a variety of equally valid methods of finding patterns, the book presents methods in their purest form so that readers can choose the method or combination that best fits their applications. The contributions are organized into three parts: Finding Patterns in DNA and Protein Sequences; Finding Patterns in 3D Structures, and System Components for Discovery. This resource is essential to anyone who conducts research in biocomputing, and can serve as an excellent supplementary text for biocomputing courses.
Because there are a variety of equally valid methods of finding patterns, the book presents methods in their purest form so that readers can choose the method or combination that best fits their applications. The contributions are organized into three parts: Finding Patterns in DNA and Protein Sequences; Finding Patterns in 3D Structures, and System Components for Discovery. This resource is essential to anyone who conducts research in biocomputing, and can serve as an excellent supplementary text for biocomputing courses.
More details
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Illustrations
numerous halftones and line figures
Dimensions
Height: 231 mm
Width: 155 mm
Thickness: 23 mm
Weight
567 gr
ISBN-13
978-0-19-511940-4 (9780195119404)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Jason T. L. Wang | Bruce A. Shapiro | Dennis Shasha
Pattern Discovery in Biomolecular Data
Tools, Techniques, and Applications
E-Book
10/1999
1st Edition
OUP eBook
€97.49
Available for download

Jason T. L. Wang | Bruce A. Shapiro | Dennis Shasha
Pattern Discovery in Biomolecular Data
Tools, Techniques, and Applications
E-Book
10/1999
1st Edition
OUP eBook
€97.49
Available for download
Persons
Editor
Department of Computer and Information ScienceDepartment of Computer and Information Science, New Jersey Institute of Technology
Lab of Mathematical BiologyLab of Mathematical Biology, National Cancer Institute
Department of Computer ScienceDepartment of Computer Science, Courant Institute of Mathematical Science, New York University
Content
Contributors
Introduction
Part I. Finding Patterns in Sequences
1: Aleksandar Milosavljevi'c: Discovering Patterns in DNA Sequences by the Algorithmic Significance Method
2: Jorja G. Henikoff: Assembling Blocks
3: Timothy L. Bailey et al.: MEME, MAST, and Meta-MEME: New Tools for Motif Discovery in Protein Sequences
4: Jason T. L. Wang et al.: Pattern Discovery and Classification in Biosequences
Part II. Finding Patterns in 3D Structures
5: Janice Glasgow, Evan Steeg, and Suzanne Fortier: Motif Discovery in Protein Structure Databases
6: Kentaro Tomii and Minoru Kanehisa: Systematic Detection of Protein Structural Motifs
7: Isidore Rigoutsos et al.: Representation and Matching of Small Flexible Molecules in Large Databases of 3D Molecular Information
Part III. System Components for Discovery
8: Bin Li, Dennis Shasha, and Jason T. L. Wang: A Framework for Biological Pattern Discovery on Networks of Workstations
9: Diane J. Cook, Lawrence B. Holder, and Gehad Galal: Discovering Concepts in Structural Data
10: David P. Yee et al.: Overview: A System for Tracking and Managing the Results from Sequence Comparison Programs
11: Bruce A. Shapiro et al.: RNA Structure Analysis: A Multifaceted Approach
Glossary
References
Index
Introduction
Part I. Finding Patterns in Sequences
1: Aleksandar Milosavljevi'c: Discovering Patterns in DNA Sequences by the Algorithmic Significance Method
2: Jorja G. Henikoff: Assembling Blocks
3: Timothy L. Bailey et al.: MEME, MAST, and Meta-MEME: New Tools for Motif Discovery in Protein Sequences
4: Jason T. L. Wang et al.: Pattern Discovery and Classification in Biosequences
Part II. Finding Patterns in 3D Structures
5: Janice Glasgow, Evan Steeg, and Suzanne Fortier: Motif Discovery in Protein Structure Databases
6: Kentaro Tomii and Minoru Kanehisa: Systematic Detection of Protein Structural Motifs
7: Isidore Rigoutsos et al.: Representation and Matching of Small Flexible Molecules in Large Databases of 3D Molecular Information
Part III. System Components for Discovery
8: Bin Li, Dennis Shasha, and Jason T. L. Wang: A Framework for Biological Pattern Discovery on Networks of Workstations
9: Diane J. Cook, Lawrence B. Holder, and Gehad Galal: Discovering Concepts in Structural Data
10: David P. Yee et al.: Overview: A System for Tracking and Managing the Results from Sequence Comparison Programs
11: Bruce A. Shapiro et al.: RNA Structure Analysis: A Multifaceted Approach
Glossary
References
Index