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Bioinformatics Computing

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Bioinformatics Computing


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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


  • Copyright 2003
  • Dimensions: 7 x 9 3/4
  • Pages: 439
  • Edition: 1st
  • Book
  • ISBN-10: 0-13-100825-0
  • ISBN-13: 978-0-13-100825-0

The complete, practical guide to bioinformatics for molecular biologists and life scientists

  • Gives an overview of bioinformatics from a computer science perspective
  • Makes the computer science aspects of bioinformatics more understandable for life scientists.
  • Presents a ready reference for current and future online and standalone tools

In 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" advances
  • Bioinformatics information infrastructure, including GENBANK and other Web-based resources
  • Very large biological databases: object-oriented database methods, data mining/warehousing, knowledge management, and more
  • 3D visualization: exploring the inner workings of complex biological structures
  • Advanced pattern matching techniques, including microarray research and gene prediction
  • Event-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.

Sample Content

Online Sample Chapter

Understanding Networking in Bioinformatics Information

Table of Contents



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.




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