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.

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