|
Bioinformatics Computing
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.
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.
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.
|
