Statistical Network Genetics
Evolutionary Game Theory in Action
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Statistical Network Genetics: Evolutionary Game Theory in Action offers an interdisciplinary integration of statistical genetics and evolutionary game theory using the latest data, codes and computational functions. While classic statistical genetics attempts to identify and map individual key genes, proteins or metabolites associated with complex traits, this book examines how entities interact with each other through this complex, yet well-orchestrated set of networks for mediating phenotypic variation. In addition, the book covers genetic and genomic networking across ecological, environmental and evolutionary factors. Written by leading experts on game theory and statistical genetics, this book introduces elements from multiple disciplines, including community ecology, network theory and physics theory, tying them into statistical model examples. It provides a platform for previously disjointed ideas and concepts of evolutionary game theory and its role in statistical genetics. This is the ideal resource for evolutionary and computational biologists, especially those seeking a thorough and current understanding of the connection to statistical genetics.
Key Features
- Examines and describes state-of-the-art approaches for maximizing statistical genetic research
- Provides usable computer codes for readers to practice statistical methods described in the chapters
- Features expert analysis of high-dimensional data for linking genotypes to phenotypes, emphasizing the role of omics data to understanding phenotypic formation
Readership
Researching and practicing evolutionary biologists; computer scientists; evolutionary mathematicians
Advanced undergraduate or graduate students in evolutionary biology, statistical genetics, computer science, or evolutionary mathematics disciplines
Advanced undergraduate or graduate students in evolutionary biology, statistical genetics, computer science, or evolutionary mathematics disciplines
Table of Contents
- 1. Statistical Genetics: Current Status
2. Functional Mapping Meets Evolutionary Game Theory
3. Systems Evolutionary Game Network Model
4. Extracting Dynamic Networks from Static Snapshots
5. Genetic Networks of Genomic Networks
6. Multiplex Networks across Spaces
7. Multilayer Networks
8. Genetic Networks of Ecological Networks
9. Genome-wide by Environment Interaction Networks
10. Statistical Genetics: Future Directions
Product details
- No. of pages: 225
- Language: English
- Copyright: © Academic Press 2023
- Published: January 1, 2023
- Imprint: Academic Press
- Paperback ISBN: 9780323988018
About the Editor
Rongling Wu
Dr. Rongling Wu is a Distinguished Professor and the Director of the Center for Statistical Genetics at The Pennsylvania State University. He continues to collaborate with his previous institution, the Beijing Forestry University. He 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. He has developed functional mapping to reveal the genetic architecture of developmental trajectories and integrated this approach into the context of evo-devo research into evolutionary novelties. Recently, he has introduced game theory into complex-trait mapping, from which a systems evolutionary game network theory is proposed to strengthen and broaden the field of quantitative genetics. Dr. Wu’s work has been cited and highlighted by top journals.
Affiliations and Expertise
Professor and the Director of the Center for Statistical Genetics, The Pennsylvania State University, USA