Bioinformatics Computing

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Edition: 1st
Format: Paperback
Pub. Date: 2002-11-19
Publisher(s): Prentice Hall
List Price: $54.99

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Summary

The complete, practical guide to bioinformatics for molecular biologists and life scientistsGives an overview of bioinformatics from a computer science perspectiveMakes the computer science aspects of bioinformatics more understandable for life scientists.Presents a ready reference for current and future online and standalone toolsIn "Bioinformatics Computing," Harvard Medical School and MIT faculty member Bryan Bergeron presents a comprehensive and practical guide to bioinformatics for life scientists at every level of training and practice. After an up-to-the-minute overview of the entire field, he illuminates every key bioinformatics technology, offering practical insights into the full range of bioinformatics applications-both new and emerging. Coverage includes: Technologies that enable researchers to collaborate more effectively Fundamental concepts, state-of-the-art tools, and "on the horizon" advancesBioinformatics information infrastructure, including GENBANK and other Web-based resourcesVery large biological databases: object-oriented database methods, data mining/warehousing, knowledge management, and more3D visualization: exploring the inner workings of complex biological structuresAdvanced pattern matching techniques, including microarray research and gene predictionEvent-driven, time-driven, and hybrid simulation techniques"Bioinformatics Computing" combines practical insight for assessing bioinformatics technologies, practical guidance for using them effectively, and intelligent context for understanding their rapidly evolving roles.

Author Biography

Bryan Bergeron is a faculty member at both Harvard Medical School and Massachusetts Institute of Technology, editor-in-chief of e.MD, editorial board member of Healthcare Informatics, and Fellow of the American College of Medical Informatics.

Table of Contents

Preface.
Acknowledgments.
1. The Central Dogma.
The Killer Application. Parallel Universes. Watson's Definition. Top-Down Versus Bottom-Up. Information Flow. Convergence. Endnote.

2. Databases.
Definitions. Data Management. Data Life Cycle. Database Technology. Interfaces. Implementation. Endnote.

3. Networks.
Geographical Scope. Communications Models. Transmissions Technology. Protocols. Bandwidth. Topology. Hardware. Contents. Security. Ownership. Implementation. Management. On the Horizon. Endnote.

4. Search Engines.
The Search Process. Search Engine Technology. Searching and Information Theory. Computational Methods. Search Engines and Knowledge Management. On the Horizon. Endnote.

5. Data Visualization.
Sequence Visualization. Structure Visualization. User Interface. Animation Versus Simulation. General-Purpose Technologies. One the Horizon. Endnote.

6. Statistics.
Statistical Concepts. Microarrays. Imperfect Data. Basics. Quantifying Randomness. Data Analysis. Tool Selection. Statistics of Alignment. Clustering and Classification. On the Horizon. Endnote.

7. Data Mining.
Methods. Technology Overview. Infrastructure. Pattern Recognition and Discovery. Machine Learning. Text Mining. Tools. On the Horizon. Endnote.

8. Pattern Matching.
Fundamentals. Dot Matrix Analysis. Substitution Matrices. Dynamic Programming. Word Methods. Multiple Sequence Alignment. Tools. On the Horizon. Endnote.

9. Modeling and Simulation.
Drug Discovery. Fundamentals. Protein Structure. Systems Biology. Tools. On the Horizon. Endnote.

10. Collaboration.
Collaboration and Communications. Standards. Issues. On the Horizon. Endnote.

Bibliography.
Index.

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