Bioinformatics computing

Bryan Bergeron9780131008250, 9780131632127, 0131008250, 0131632124

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.

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Table of contents :
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