Cover -- Title Page -- Copyright Page -- Dedication -- Contents -- Contributors -- Introduction -- Part I. Finding Patterns in Sequences -- 1. Discovering Patterns in DNA Sequences by the Algorithmic Significance Method -- 1.1. Encoding Schemes -- 1.2. Algorithms for Minimal Length Encoding -- 1.3. Algorithmic Significance -- 1.4. Applications -- 1.5. Future Work and Generalizations -- 2. Assembling Blocks -- 2.1. Algorithmic Techniques -- 2.2. Future Work and Generalizations -- 3. MEME, MAST, and Meta-MEME: New Tools for Motif Discovery in Protein Sequences -- 3.1. Software for Finding Sequence Motifs -- 3.2. Methods -- 3.3. Results -- 3.4. Discussion -- 4. Pattern Discovery and Classification in Biosequences -- 4.1. Pattern Discovery in Protein Sequences -- 4.2. Classification of DNA Sequences -- 4.3. Generalizations and Future Work -- Part II. Finding Patterns in 3D Structures -- 5. Motif Discovery in Protein Structure Databases -- 5.1. Protein Motifs -- 5.2. Computational Approaches to Knowledge Discovery -- 5.3. Assessing Protein Motifs and Discovery Methods -- 5.4. Issues in Protein Motif Discovery -- 5.5. Conclusion -- 6. Systematic Detection of Protein Structural Motifs -- 6.1. Structural Building Blocks -- 6.2. Symbol String Representation of 3D Structures -- 6.3. Detection of Structural Motifs by Structure Comparisons -- 6.4. Detection of Structural Motifs by Sequence Comparisons -- 6.5. Discussion and Future Directions -- 7. Representation and Matching of Small Flexible Molecules in Large Databases of 3D Molecular Information -- 7.1. The Representation Scheme -- 7.2. Storage/Retrieval and Threading -- 7.3. The Algorithm -- 7.4. Experimental Results -- 7.5. Discussion -- Part III. System Components for Discovery -- 8. A Framework for Biological Pattern Discovery on Networks of Workstations -- 8.1. Biological Pattern Discovery.

8.2. Biological Pattern Discovery Framework -- 8.3. Parallel Computing on Networks of Workstations -- 8.4. Parallel E-dag Traversal in PLinda -- 9. Discovering Concepts in Structural Data -- 9.1. Algorithmic Techniques -- 9.2. Future Work and Generalizations -- 10. Overview: A System for Tracking and Managing the Results from Sequence Comparison Programs -- 10.1. Related Work -- 10.2. Molecular Biology Applications and Databases -- 10.3. Algorithmic Techniques -- 10.4. The Overview Information Model -- 10.5. Biological Experiments and Applications: User Scenarios -- 10.6. Future Work and Generalizations -- 11. RNA Structure Analysis: A Multifaceted Approach -- 11.1. A Brief Introduction to RNA -- 11.2. RNA Folding Problem -- 11.3. The Genetic Algorithm: An Overview -- 11.4. The Structurelab Workbench -- 11.5. Structurelab in Use -- 11.6. Future Directions and Challenges -- Glossary -- References -- Index.