Description
Translational 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
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Chapter
ONE - Concept and Basic Tools
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
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”
2.3.1 Emergence and Interaction Patterns: Human-Centered Medicine
2.3.2 Adaptation and Coevolution: The Dynamical Processes
2.3.3 Self-Organization and Feedback Loops: The Robust Networks
2.3.4 Nonlinearity and Dynamical Pathophysiology
2.4 SYSTEMS AND DYNAMICAL MEDICINE WITH P4 FEATURES
THREE - Translational Bioinformatics Support for “Omics” Studies: Methods and Resources
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
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
4.2.1 The Basic Data Integration Steps
4.2.2 Bioinformatics and Health Informatics Resources for Standardization
4.2.3 The Integration of Biological and Medical Informatics
4.3 DATA MINING AND KNOWLEDGE DISCOVERY IN TRANSLATIONAL BIOINFORMATICS
4.4 CONCLUSION: DECISION SUPPORT IN TRANSLATIONAL BIOINFORMATICS
TWO - Applications in Basic Sciences
FIVE - Applying Translational Bioinformatics for Biomarker Discovery
5.1 INTRODUCTION: CONCEPTS AND APPROACHES
5.1.1 The Basic Concepts and Types of Biomarkers
5.1.2 Steps and Pipelines of Biomarker Discovery
5.1.3 The Clinical Values of Biomarkers
5.2 CHALLENGES AND TRANSLATIONAL BIOINFORMATICS METHODS FOR BIOMARKER DISCOVERY
5.3 FINDING ROBUST BIOMARKERS FOR SYSTEMS AND DYNAMICAL MEDICINE
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
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
THREE - Applications in Clinical and Translational Sciences
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
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
9.4.1 Infectious Diseases
9.4.2 Inflammatory Bowel Disease/Crohn’s Disease
9.4.3 Autoimmune Diseases
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
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
11.4.1 Cancer Metastasis and Biomarkers
11.4.2 Dynamical Biomarkers for Cancers
11.4.3 Examples in Breast Cancer
11.4.4 Examples in Lung Cancer
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
12.4.2 Dynamical Biomarkers for Alzheimer’s Disease
Translational Bioinformatics and Systems Biology Methods for Personalized Medicine
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