Bioinformatics computing : and introduction to bioinformatics

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. Bioinformatics Computing......Page 1 Table of Contents......Page 2 Copyright......Page 5 About Prentice Hall Professional Technical Reference......Page 7 Preface......Page 8 Organization of This Book......Page 11 How to Use This Book......Page 13 The Larger Context......Page 14 Acknowledgments......Page 15 Chapter 1. The Central Dogma......Page 16 The Killer Application......Page 18 Parallel Universes......Page 21 Watson's Definition......Page 26 Top-Down Versus Bottom-Up......Page 30 Information Flow......Page 34 Convergence......Page 39 Endnote......Page 49 Chapter 2. Databases......Page 51 Definitions......Page 56 Data Management......Page 59 Data Life Cycle......Page 71 Database Technology......Page 78 Interfaces......Page 92 Implementation......Page 95 Endnote......Page 99 Chapter 3. Networks......Page 100 Geographical Scope......Page 106 Communications Models......Page 108 Transmissions Technology......Page 109 Protocols......Page 111 Bandwidth......Page 114 Topology......Page 116 Hardware......Page 118 Contents......Page 126 Security......Page 127 Ownership......Page 131 Implementation......Page 132 Management......Page 134 On the Horizon......Page 135 Endnote......Page 136 Chapter 4. Search Engines......Page 137 The Search Process......Page 141 Search Engine Technology......Page 147 Searching and Information Theory......Page 153 Computational Methods......Page 157 Search Engines and Knowledge Management......Page 161 On the Horizon......Page 164 Endnote......Page 165 Chapter 5. Data Visualization......Page 166 Sequence Visualization......Page 171 Structure Visualization......Page 175 User Interface......Page 187 Animation Versus Simulation......Page 196 General-Purpose Technologies......Page 197 On the Horizon......Page 199 Endnote......Page 200 Chapter 6. Statistics......Page 201 Statistical Concepts......Page 203 Microarrays......Page 207 Imperfect Data......Page 216 Basics......Page 221 Quantifying Randomness......Page 226 Data Analysis......Page 228 Tool Selection......Page 233 Statistics of Alignment......Page 236 Clustering and Classification......Page 237 On the Horizon......Page 240 Endnote......Page 241 Chapter 7. Data Mining......Page 242 Methods......Page 245 Technology Overview......Page 252 Infrastructure......Page 253 Pattern Recognition and Discovery......Page 255 Machine Learning......Page 257 Text Mining......Page 268 Tools......Page 273 On the Horizon......Page 275 Endnote......Page 277 Chapter 8. Pattern Matching......Page 278 Fundamentals......Page 281 Dot Matrix Analysis......Page 286 Substitution Matrices......Page 288 Dynamic Programming......Page 292 Word Methods......Page 300 Bayesian Methods......Page 302 Multiple Sequence Alignment......Page 303 Tools......Page 305 On the Horizon......Page 315 Endnote......Page 316 Chapter 9. Modeling and Simulation......Page 317 Drug Discovery......Page 322 Fundamentals......Page 324 Protein Structure......Page 338 Systems Biology......Page 353 Tools......Page 354 On the Horizon......Page 355 Endnote......Page 356 Chapter 10. Collaboration......Page 357 Collaboration and Communications......Page 359 Standards......Page 366 Issues......Page 373 On the Horizon......Page 377 Endnote......Page 378 Bibliography......Page 381 Chapter One-The Central Dogma......Page 382 Chapter Two-Databases......Page 384 Chapter Three-Networks......Page 385 Chapter Four-Search Engines......Page 386 Chapter Five-Data Visualization......Page 387 Chapter Six-Statistics......Page 388 Chapter Seven-Data Mining......Page 389 Chapter Eight-Pattern Matching......Page 390 Chapter Nine-Modeling and Simulation......Page 391 Chapter Ten-Collaboration......Page 393 index......Page 394 SYMBOL......Page 395 Team FOS......Page 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.

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 Comprehensive and concise, this handbook has chapters on computing visualization, large database designs, advanced pattern matching and other key bioinformatics techniques. It 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