Buch, Englisch, 225 Seiten, Format (B × H): 191 mm x 234 mm
Evolutionary Game Theory in Action
Buch, Englisch, 225 Seiten, Format (B × H): 191 mm x 234 mm
ISBN: 978-0-323-98801-8
Verlag: Elsevier Science
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.
Zielgruppe
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
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
1. Statistical Genetics: Current Status2. Functional Mapping Meets Evolutionary Game Theory3. Systems Evolutionary Game Network Model4. Extracting Dynamic Networks from Static Snapshots5. Genetic Networks of Genomic Networks 6. Multiplex Networks across Spaces7. Multilayer Networks8. Genetic Networks of Ecological Networks9. Genome-wide by Environment Interaction Networks10. Statistical Genetics: Future Directions