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.
Features :
NEW--Brings together all of the latest advances in computing for biological research--Including visualization,
large database design, advanced pattern matching, statistical methods, distributed computing--and places these
advances in context.
Provides a single source for students who want to understand the full field of bioinformatics, and choose the
right tools and technologies for their own research.
By one of the world's leading experts in technology for medical research--By Bryan Bergeron, faculty member
at Harvard Medical School and MIT, Editor-in-Chief of e.MD, and Healthcare Informatics editorial board member.
Lets students learn from an expert with a profound understanding of bioinformatics and an exceptional ability
to explain both the technologies and their implications.
Bioinformatics advances on the near horizon--Covers technologies and approaches that will soon have a major
impact on bioinformatics practitioners.
Helps students anticipate foreseeable changes in bioinformatics, so they can prepare to take advantage of them.
Global and societal drivers of bioinformatics--Reviews the key global and societal issues that are most likely
to shape the field of bioinformatics.
Helps students understand bioinformatics in its broadest context--and understand the non-technical issues that
are likely to affect which technologies become available and how they are used.
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.
