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Bioinformatics Computing
- By Bryan Bergeron
- Published Nov 19, 2002 by Pearson.
Book
- Sorry, this book is no longer in print.
About
Features
A comprehensive introduction to computing techniques for Molecular Biologists
° Bioinformatics is an IT growth sector ($10.4 Billion in 2000, forecasted to $38 Billion
by 2006)
° Chapters on computing visualization, large database designs, advanced pattern
matching and other key bioinformatics techniques
° Bryan Bergeron is on the faculty at both Harvard Medical School and MIT
Description
- Copyright 2003
- Dimensions: 7" x 9-1/4"
- Pages: 464
- Edition: 1st
- Book
- ISBN-10: 0-13-100825-0
- ISBN-13: 978-0-13-100825-0
Bioinformatics Computing is a practical guide to computing in the growing field of Bioinformatics (the study of how information is represented and transmitted in biological systems, starting at the molecular level). This book brings life scientists at every level - from students to research directors - up to speed in computational techniques that apply directly to their work. The life science community needs a practical guide that illustrates the computer science advances that have been made in the past several decades in areas of computer visualization, large database designs, machine learning and other forms of advanced pattern matching, statistical methods, and distributed computing techniques. In addition to exploring general information technology issues, each chapter identifies technologies and approaches on the near horizon that will have a significant impact on bioinformatics, and introduces some of the global, societal issues that will likely define bioinformatics developments in the future.
Extras
Related Articles
Applied Bioinformatics Computing: An Introduction
Applied Bioinformatics Computing: Data Mining
Sample Content
Online Sample Chapter
Understanding Networking in Bioinformatics Information
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.