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Translational Bioinformatics and Systems Biology Methods for Personalized Medicine
- 1st Edition - April 18, 2017
- Author: Qing Yan
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 0 4 3 2 8 - 8
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 0 4 3 8 8 - 2
Translational Bioinformatics and Systems Biology Methods for Personalized Medicine introduces integrative approaches in translational bioinformatics and systems biology to suppor… Read more
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Request a sales quoteTranslational Bioinformatics and Systems Biology Methods for Personalized Medicine introduces integrative approaches in translational bioinformatics and systems biology to support the practice of personalized, precision, predictive, preventive, and participatory medicine. Through the description of important cutting-edge technologies in bioinformatics and systems biology, readers may gain an essential understanding of state-of-the-art methodologies.
The book discusses topics such as the challenges and tasks in translational bioinformatics; pharmacogenomics, systems biology, and personalized medicine; and the applicability of translational bioinformatics for biomarker discovery, epigenomics, and molecular dynamics. It also discusses data integration and mining, immunoinformatics, and neuroinformatics. With broad coverage of both basic scientific and clinical applications, this book is suitable for a wide range of readers who may not be scientists but who are also interested in the practice of personalized medicine.
- Introduces integrative approaches in translational bioinformatics and systems biology to support the practice of personalized, precision, predictive, preventive, and participatory medicine
- Presents a problem-solving oriented methodology to deal with practical problems in various applications
- Covers both basic scientific and clinical applications in order to enhance the collaboration between researchers and clinicians
- Brings integrative and multidisciplinary approaches to bridge the gaps among various knowledge domains in the field
Graduate students, researchers and professionals interested in bioinformatics, systems biology, personalized medicine and various biomedical areas
Part I. Concepts and Basic Tools
Chapter One. Introduction: Translational Bioinformatics and Personalized Medicine
- 1.1. Current Challenges in Biomedicine
- 1.2. Translational Bioinformatics as the “Vehicle” Toward Personalized Medicine
- 1.3. The Goals and Missions
Chapter Two. Systems and Dynamical Medicine: The Roles of Translational Bioinformatics
- 2.1. The Integration of Pharmacogenomics and Systems Biology
- 2.2. Translational Bioinformatics, Personalized and Systems Medicine
- 2.3. The Basic Concepts of the Complex “Whole Body System”
- 2.4. Systems and Dynamical Medicine With P4 Features
Chapter Three. Translational Bioinformatics Support for “Omics” Studies: Methods and Resources
- 3.1. Introduction
- 3.2. Bioinformatics Methods and Resources for “Omics” Studies
- 3.3. Bioinformatics Methods and Resources for Epigenomics and MicroRNA Studies
- 3.4. Bioinformatics Support for the Studies of Disease Phenotypes and Drug Responses
- 3.5. Bioinformatics Support for the Spatiotemporal Studies Toward Dynamical Medicine
- 3.6. Conclusion
Chapter Four. Data Integration, Data Mining, and Decision Support in Biomedical Informatics
- 4.1. Introduction: Data and Workflow Integration in Translational Bioinformatics
- 4.2. Approaches of Data and Workflow Integration
- 4.3. Data Mining and Knowledge Discovery in Translational Bioinformatics
- 4.4. Conclusion: Decision Support in Translational Bioinformatics
Part II. Applications in Basic Sciences
Chapter Five. Applying Translational Bioinformatics for Biomarker Discovery
- 5.1. Introduction: Concepts and Approaches
- 5.2. Challenges and Translational Bioinformatics Methods for Biomarker Discovery
- 5.3. Finding Robust Biomarkers for Systems and Dynamical Medicine
Chapter Six. Biomarkers From Systems Biology and “Omics” Studies: Applications and Examples
- 6.1. Proteomic and Metabolomic Pathways and Biomarkers
- 6.2. Pathways as Potential Biomarkers: Examples
- 6.3. Potential microRNA Biomarkers and Examples
- 6.4. Dynamical Circadian Biomarkers and Chronotherapy
Chapter Seven. Understanding Dynamical Diseases: Translational Bioinformatics Approaches
- 7.1. Spatial Complexity in Systems Biology
- 7.2. Temporal Complexity in Systems Biology
- 7.3. Profiling of Dynamical Diseases for Systems and Dynamical Medicine
- 7.4. Translational Bioinformatics Methods for Studying Dynamical Diseases
Part III. Applications in Clinical and Translational Sciences
Chapter Eight. Translational Bioinformatics Methods for Drug Discovery and Development
- 8.1. Challenges in Drug Discovery and Potential Solutions From Profiling Interactomes
- 8.2. The “Translational” Side and the “Bioinformatics” Side
- 8.3. Translational Bioinformatics Resources for Drug Discovery and Development
- 8.4. Translational Bioinformatics Methods for Drug Discovery and Development
- 8.5. Conclusion: Systems-Based Models and Decision Support for Drug Discovery
Chapter Nine. Translational Bioinformatics and Systems Biology for Understanding Inflammation
- 9.1. Introduction: Systems Biology, Translational Bioinformatics, and Inflammation
- 9.2. The Microbiota–Gut–Brain Axis and Systemic Inflammation
- 9.3. Translational Bioinformatics Methods for the Studies of Inflammation
- 9.4. Identifying Systems-Based Biomarkers for Inflammation: Examples
Chapter Ten. Cardiovascular Diseases and Diabetes: Translational Bioinformatics and Systems Biology Methods
- 10.1. Translational Bioinformatics Methods for Studies in Cardiovascular Diseases
- 10.2. Lipidomics, Computational Systems Biology, and Drug Repositioning
- 10.3. Nutritional Systems Biology, Biomarkers, and Type 2 Diabetes
- 10.4. Finding Systems-Based Biomarkers for Cardiovascular Diseases: Examples
- 10.5. Finding Systems-Based Dynamical Biomarkers for Diabetes: Examples
Chapter Eleven. Translational Bioinformatics and Systems Biology for Cancer Precision Medicine
- 11.1. Introduction: Systems Biology, Cancer Precision Medicine, and Immunotherapy
- 11.2. Translational Bioinformatics Resources for Cancer Studies
- 11.3. Translational Bioinformatics Methods for Cancer Studies
- 11.4. Identifying Potential Systems-Based Biomarkers for Cancers
Chapter Twelve. Aging and Age-Associated Diseases: Translational Bioinformatics and Systems Biology Methods
- 12.1. Introduction: Challenges and Opportunities in Aging Studies
- 12.2. Resources and Methods in Translational Bioinformatics for Aging Studies
- 12.3. Comprehensive “Omics” Profiling for Neurodegenerative Diseases
- 12.4. Finding Potential Systems-Based Biomarkers for Aging and Associated Diseases
- No. of pages: 182
- Language: English
- Edition: 1
- Published: April 18, 2017
- Imprint: Academic Press
- Paperback ISBN: 9780128043288
- eBook ISBN: 9780128043882
QY
Qing Yan
Dr. Qing Yan has extensive research experience in translational bioinformatics and systems biology, including more than 14 years as a group leader in the biopharmaceutical industry. He has published numerous research papers and book chapters, and edited six biomedical books including Systems Biology in Drug Discovery and Development: Methods and Protocols and Pharmacogenomics in Drug Discovery and Development.
Dr. Yan received a Ph.D. degree in Biological and Medical Informatics from the University of California San Francisco (UCSF).
Affiliations and expertise
Chief Scientist, PharmTao, Santa Clara, CA, USA; Adjunct Associate Professor, University of Maryland University College, Adelphi, MD, USARead Translational Bioinformatics and Systems Biology Methods for Personalized Medicine on ScienceDirect