Bioinformatics Computing


  • Author: Bryan Bergeron
  • Co-Author: M.D
  • Publisher: PHI
  • ISBN-13: 9788120322585
  • Binding: Paperback
  • Pages: 462
  • Year of Pub / Reprint Year: 2003


About the Book:

Appropriate for all courses in bioinformatics, for molecular biology students at all levels.
The field of bioinformatics is growing at an unprecedented rate, as molecular biologists discover the extraordinary range of computational techniques and applications that apply directly to their work. Now, Harvard Medical School and MIT faculty member Bryan Bergeron has written a comprehensive, practical guide to bioinformatics for biology students at every level. Bergeron illuminates key advances in computer visualization, large database design, advanced pattern matching, machine learning, statistical methods, and distributed computing—and demonstrates exactly how these advances can be used to advance research into biological systems. Bergeron also identifies technologies and approaches on the near horizon that will have a significant impact on bioinformatics, and introduces the key global and societal issues most likely to shape bioinformatics in the coming years.

Table of Content:
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.