The field molecular pathway analysis evolves rapidly, and many progressive methods have recently been discovered. Molecular Pathway Analysis Using High-Throughput OMICS Data contains the largest collections of molecular pathways. For the first time, guidelines on how to do genomic, epigenetic, transcriptomic, proteomic, and metabolomic data analysis in real-world research practice are given. Molecular Pathway Analysis Using High-Throughput OMICS Molecular Data also focuses on the pathway analysis applications for solving tasks in biotechnology, pharmaceutics, and molecular diagnostics It demonstrates how pathway analysis can be applied for the research and treatment of chronic and acute diseases, for next-generation molecular diagnostics, for drug design and preclinical testing; relevant real-world examples, molecular tests, and web resources will be reviewed in-depth. The book shows a tendency of erasing the borders between chemistry, physics, informatics, mathematics, biology, and medicine by means of novel research approaches and instruments, providing a truly multidisciplinary approach.
1. Molecular Pathway Analysis Using High-Throughput OMICS Molecular Data - p. Page i 2. Cover - p. Page i 3. Front Matter - p. Page ii 4. Table of Contents - p. Page iii 5. Copyright - p. Page iv 6. Dedication - p. Page v 7. Contributors - p. Page v 8. About the editor - p. Page vii 9. Preface - p. Page viii 10. List of Illustrations - p. Page ix 11. List of Tables - p. Page x 12. Chapter 1 : Past, current, and future of molecular pathway analysis - p. Page x 13. Chapter 2 : Molecular data for the pathway analysis - p. Page 22 14. Chapter 3 : Benefits and challenges of OMICS data integration at the pathway level - p. Page 52 15. Chapter 4 : Controls for the molecular data: Normalization, harmonization, and quality thresholds - p. Page 89 16. Chapter 5 : Reconstruction of molecular pathways - p. Page 113 17. Chapter 6 : Qualitative and quantitative molecular pathway analysis: Mathematical methods and algorithms - p. Page 147 18. Chapter 7 : Getting started with the molecular pathway analysis - p. Page 169 19. Chapter 8 : Molecular pathway analysis using comparative genomic and epigenomic data - p. Page 192 20. Chapter 9 : Quantitative molecular pathway analysis using transcriptomic and proteomic data - p. Page 225 21. Chapter 10 : MicroRNA data for quantitative analysis of molecular pathways - p. Page 249 22. Chapter 11 : Methods and tools for OMICS data integration - p. Page 266 23. Chapter 12 : Molecular pathway approach in clinical oncology - p. Page 292 24. Chapter 13 : Molecular pathway approach in pharmaceutics - p. Page 316 25. Chapter 14 : Molecular pathway approach in biotechnology - p. Page 332 26. Chapter 15 : Molecular pathway approach in biology and fundamental medicine - p. Page 347 27. Index - p. Page 371
The field molecular pathway analysis evolves rapidly, and many progressive methods have recently been discovered. Molecular Pathway Analysis Using High-Throughput OMICS Data contains the largest collections of molecular pathways. For the first time, guidelines on how to do genomic, epigenetic, transcriptomic, proteomic, and metabolomic data analysis in real-world research practice are given. Molecular Pathway Analysis Using High-Throughput OMICS Molecular Data also focuses on the pathway analysis applications for solving tasks in biotechnology, pharmaceutics, and molecular diagnostics It demonstrates how pathway analysis can be applied for the research and treatment of chronic and acute diseases, for next-generation molecular diagnostics, for drug design and preclinical testing; relevant real-world examples, molecular tests, and web resources will be reviewed in-depth. The book shows a tendency of erasing the borders between chemistry, physics, informatics, mathematics, biology, and medicine by means of novel research approaches and instruments, providing a truly multidisciplinary approach.
1. Molecular Pathway Analysis Using High-Throughput OMICS Molecular Data - p. Page i 2. Cover - p. Page i 3. Front Matter - p. Page ii 4. Table of Contents - p. Page iii 5. Copyright - p. Page iv 6. Dedication - p. Page v 7. Contributors - p. Page v 8. About the editor - p. Page vii 9. Preface - p. Page viii 10. List of Illustrations - p. Page ix 11. List of Tables - p. Page x 12. Chapter 1 : Past, current, and future of molecular pathway analysis - p. Page x 13. Chapter 2 : Molecular data for the pathway analysis - p. Page 22 14. Chapter 3 : Benefits and challenges of OMICS data integration at the pathway level - p. Page 52 15. Chapter 4 : Controls for the molecular data: Normalization, harmonization, and quality thresholds - p. Page 89 16. Chapter 5 : Reconstruction of molecular pathways - p. Page 113 17. Chapter 6 : Qualitative and quantitative molecular pathway analysis: Mathematical methods and algorithms - p. Page 147 18. Chapter 7 : Getting started with the molecular pathway analysis - p. Page 169 19. Chapter 8 : Molecular pathway analysis using comparative genomic and epigenomic data - p. Page 192 20. Chapter 9 : Quantitative molecular pathway analysis using transcriptomic and proteomic data - p. Page 225 21. Chapter 10 : MicroRNA data for quantitative analysis of molecular pathways - p. Page 249 22. Chapter 11 : Methods and tools for OMICS data integration - p. Page 266 23. Chapter 12 : Molecular pathway approach in clinical oncology - p. Page 292 24. Chapter 13 : Molecular pathway approach in pharmaceutics - p. Page 316 25. Chapter 14 : Molecular pathway approach in biotechnology - p. Page 332 26. Chapter 15 : Molecular pathway approach in biology and fundamental medicine - p. Page 347 27. Index - p. Page 371
