Rongling Wu

Quantitative Methods for Precision Medicine (eBook, ePUB)

Pharmacogenomics in Action

• Format: ePub

Produktbeschreibung

This book presents the advanced statistical methods for mapping pharmacogenetic control by integrating pharmacokinetic and pharmacodynamic principles of drug-body interactions. This book is suitable for graduate students and researchers in the field of biology, medicine, bioinformatics and drug design and delivery.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 306
• Erscheinungstermin: 26. Dezember 2022
• Englisch
• ISBN-13: 9780429528668
• Artikelnr.: 66390485

Autorenporträt

Rongling Wu develops a transdisciplinary approach for building up multilayer, multiscale and multifunctional bridges that link genotype to phenotype. Dr. Wu asks, answers, and disseminates biologically meaningful questions in the boundaries of statistics, genetics, ecology, and evolution. He invented a statistical method called functional mapping to reveal the genetic architecture of developmental trajectories and incorporated this approach into the context of eco-evo-devo research aimed to unveil the genetic and ecological mechanisms underpinning evolutionary novelties. More recently, Dr. Wu has integrated evolutionary game theory and predator-prey theory through naturally omnipresent allometric scaling law into graph theory to create a new theory - functional game-graph theory. This new theory can unravel the internal workings of complex systems at an unprecedented level of detail by charting and tracing the causal, signed, and weighted roadmap of relationships among high- or even ultrahigh-dimensional variables from any data domains. The second part of this book represents the application of this theory to pharmacogenomic research. Dr. Wu received his PhD in forest genetics at the University of Washington in 1995. He was appointed as Assistant Professor of Statistics at the University of Florida in 2000 and awarded the University Foundation Professorship in 2007. Since 2008, Dr. Wu has been Professor of Public Health Sciences and Statistics, promoted to Distinguished Professor in 2015, and served as Director of the Center of Statistical Genetics at The Pennsylvania State University. Dr. Wu is a Fellow of the American Statistical Association and a Fellow of American Association for the Advancement of Science.

Dr. Sang and Ms. Feng are collaborators of this book writing project under the leadership of Dr. Wu. Dr. Sang got his PhD degree at Beijing Forestry University in 2019 and is currently working as Lecturer of Medical Informatics at Nantong University Medical School, China. Ms. Feng is a PhD candidate in computational biology at Beijing Forestry University and going to graduate in 2023. The research interest of both Dr. Sang and Ms. Feng lies in the statistical modeling of computational biology and its applications to a broader area of agriculture, forestry, medicine, and beyond.

Inhaltsangabe

1. Methodological Foundation of Precision Medicine. 1.1. Interpersonal
variability in drug response. 1.2. Mechanistic modelling of drug response.
1.3 Statistical models for mapping drug response. 1.4 Network mapping of
drug response. 1.5 Conclusions and Outlook. Part I:
Pharmacokinetic-Pharmacodynamic Pharmacogenetics. 2. Pharmacogenetic
Dissection by Functional Mapping. 2.1. Introduction. 2.2. Quantitative
Genetics. 2.3. A General Framework for Functional Mapping. 2.4
Pharmacogenetic Application of Functional Mapping. 2.5. High-dimensional
Functional Mapping. 2.6. Concluding Remarks. 3. A Multiscale Model of
Pharmacokinetic-Pharmacodynamic Mapping. 3.3. Heterochronopharmacodynamic
Mapping. 3.4. Mapping Multifaceted Drug Reactions. 3.5. Concluding Remarks.
4. Pharmacogenetic Mapping of Missing Longitudinal Data. 4.1 Introduction.
4.2. Strategies for Modeling Non-Ignorable Dropout Data. 4.3. Haplotyping
Drug Response Using the Pattern-Mixture Model. 4.4. Haplotyping Drug
Response Using the Selection Model. 4.5. Concluding Remarks. 5. Systems
Mapping of Drug Response. 5.1. Introduction. 5.2. ODE Modeling of PK/PD
Machineries. 5.3. Systems Mapping: Model and Algorithm. 5.4. Stochastic
Systems Mapping. 5.5. Concluding Remarks. Part II. Network
Pharmacogenetics. 6. Network Mapping of Drug Response. 6.1. Introduction.
6.2. Functional Graph Theory. 6.3. Functional Pharmacogenetic Interaction
Networks: An Example. 6.4. Fine-Grained Dissection of Pharmacogenetic
Networks. 6.5. Modularity Theory and Dunbar's law. 6.6. Concluding Remarks.
7. Learning Individualized Pharmacogenetic Networks. 7.1. Introduction.
7.2. A Framework for Network Inference. 7.3. Coalescing Individualized
Networks into Stratification-Specific Networks. 7.4. Computer Simulation.
7.5. Reconstructing Multilayer Genetic Networks. 7.6. Concluding Remarks.
8. A Game-Theoretic Model of Cell Crosstalk in Drug Response. 8.1.
Introduction. 8.2. GameTalker: A crosstalk model of tumor-microenvironment
interactions. 8.3. Modeling Personalized Cell-Cell Interaction Networks.
8.4. Reconstructing multilayer gene regulatory networks of tumor-TME
interactions. 8.5. Predictive network model for cancer growth. 8.6
Concluding Remarks. 9. A Graph Model of Personalized Drug-Drug
Interactions. 9.1. Introduction. 9.2. Inferring DDI networks. 9.3.
Inferring dynamic DDI networks from static data. 9.4. Coalescing high-order
DDIs into hypernetworks. 9.5. Learning Large-scale DDI Networks. 9.6.
Concluding remarks. 10. Pharmacogenomics as a Cornerstone of Precision
Medicine: Methodological Leveraging. 10.1. Introduction. 10.2. How Drug
Works. 10.3. Correcting for Relatedness in Pharmacogenomics GWAS. 10.4
Family-based Designs for PGx Studies. 10.5. Intertwined Epistatic and
Epistatic Networks. 10.6. Pharmacosystems Biology: from Pharmacogenomics to
Pharmaco-Omics. 10.7. Concluding Remarks.