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Buch, Englisch, 320 Seiten, Format (B × H): 161 mm x 235 mm, Gewicht: 572 g
Buch, Englisch, 320 Seiten, Format (B × H): 161 mm x 235 mm, Gewicht: 572 g
Reihe: IEEE Press Series on Biomedical Engineering
ISBN: 978-0-471-63181-1
Verlag: John Wiley & Sons Inc
Current applications and recent advances in genomics and proteomics
Genomics and Proteomics Engineering in Medicine and Biology presents a well-rounded, interdisciplinary discussion of a topic that is at the cutting edge of both molecular biology and bioengineering. Compiling contributions by established experts, this book highlights up-to-date applications of biomedical informatics, as well as advancements in genomics-proteomics areas. Structures and algorithms are used to analyze genomic data and develop computational solutions for pathological understanding.
Topics discussed include:
- Qualitative knowledge models
- Interpreting micro-array data
- Gene regulation bioinformatics
- Methods to analyze micro-array
- Cancer behavior and radiation therapy
- Error-control codes and the genome
- Complex life science multi-database queries
- Computational protein analysis
- Tumor and tumor suppressor proteins interactions
Autoren/Hrsg.
Fachgebiete
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Vorklinische Medizin: Grundlagenfächer Humangenetik
- Naturwissenschaften Biowissenschaften Botanik Pflanzenreproduktion, Verbreitung, Genetik
- Naturwissenschaften Biowissenschaften Tierkunde / Zoologie Tiergenetik, Reproduktion
- Naturwissenschaften Biowissenschaften Biowissenschaften Genetik und Genomik (nichtmedizinisch)
- Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Biotechnologie Medizinische Biotechnologie
- Naturwissenschaften Biowissenschaften Biowissenschaften DNA und Transgene Organismen
Weitere Infos & Material
Preface xi
Contributors xiii
1. Qualitative Knowledge Models in Functional Genomics and Proteomics 1
Mor Peleg, Irene S. Gabashvili, and Russ B. Altman
1.1. Introduction 1
1.2. Methods and Tools 3
1.3. Modeling Approach and Results 6
1.4. Discussion 19
1.5. Conclusion 20
References 21
2. Interpreting Microarray Data and Related Applications Using Nonlinear System Identification 25
Michael Korenberg
2.1. Introduction 25
2.2. Background 25
2.3. Parallel Cascade Identification 30
2.4. Constructing Class Predictors 34
2.5. Prediction Based on Gene Expression Profiling 35
2.6. Comparing Different Predictors Over the Same Data Set 46
2.7. Concluding Remarks 48
References 49
3. Gene Regulation Bioinformatics of Microarray Data 55
Gert Thijs, Frank De Smet, Yves Moreau, Kathleen Marchal, and Bart De Moor
3.1. Introduction 55
3.2. Introduction to Transcriptional Regulation 57
3.3. Measuring Gene Expression Profiles 59
3.4. Preprocessing of Data 61
3.5. Clustering of Gene Expression Profiles 63
3.6. Cluster Validation 70
3.7. Searching for Common Binding Sites of Coregulated Genes 76
3.8. Inclusive: Online Integrated Analysis of Microarray Data 87
3.9. Further Integrative Steps 89
3.10. Conclusion 90
References 91
4. Robust Methods for Microarray Analysis 99
George S. Davidson, Shawn Martin, Kevin W. Boyack, Brian N. Wylie, Juanita Martinez, Anthony Aragon, Margaret Werner-Washburne, Mónica Mosquera-Caro, and Cheryl Willman
4.1. Introduction 99
4.2. Microarray Experiments and Analysis Methods 100
4.3. Unsupervised Methods 103
4.4. Supervised Methods 117
4.5. Conclusion 127
References 128
5. In Silico Radiation Oncology: A Platform for Understanding Cancer Behavior and Optimizing Radiation Therapy Treatment 131
G. Stamatakos, D. Dionysiou, and N. Uzunoglu
5.1. Philosophiae Tumoralis Principia Algorithmica: Algorithmic Principles of Simulating Cancer on Computer 131
5.2. Brief Literature Review 133
5.3. Paradigm of Four-Dimensional Simulation of Tumor Growth and Response to Radiation Therapy In Vivo 135
5.4. Discussion 148
5.5. Future Trends 150
References 150
6. Genomewide Motif Identification Using a Dictionary Model 157
Chiara Sabatti and Kenneth Lange
6.1. Introduction 157
6.2. Unified Model 160
6.3. Algorithms for Likelihood Evaluation 164
6.4. Parameter Estimation via Minorization–Maximization Algorithm 167
6.5. Examples 170
6.6. Discussion and Conclusion 171
References 172
7. Error Control Codes and the Genome 173
Elebeoba E. May
7.1. Error Control and Communication: A Review 173
7.2. Central Dogma as Communication System 180
7.3. Reverse Engineering the Genetic Error Control System 184
7.4. Applications of Biological Coding Theory 203
References 205
8. Complex Life Science Multidatabase Queries 209
Zina Ben Miled, Nianhua Li, Yue He, Malika Mahoui, and Omran Bukhres
8.1. Introduction 209
8.2. Architecture 212
8.3. Query Execution Plans 214
8.4. Related Work 219
8.5. Future Trends 222
References 223
9. Computational Analysis of Proteins 227
Dimitrios I. Fotiadis, Yorgos Goletsis, Christos Lampros, and Costas Papaloukas
9.1. Introduction: Definitions 227
9.2. Databases 229
9.3. Sequence Motifs and Domains 232
9.4. Sequence Alignment 235
9.5. Modeling 241
9.6. Classification and Prediction 242
9.7. Natural Language Processing 248
9.8. Future Trends 252
References 252
10. Computational Analysis of Interactions Between Tumor and Tumor Suppressor Proteins 257
E. Pirogova, M. Akay, and I. Cosic
10.1. Introduction 257
10.2. Methodology: Resonant Recognition Model 261
10.3. Results and Discussions 265
10.4. Conclusion 284
References 285
Index 289
About the Editor 299




