Modeling Evolution of Heterogeneous Populations
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ISBN/EAN:
9780128144329
Modeling Evolution of Heterogeneous Populations: Theory and Applications describes, develops and provides applications of a method that allows incorporating population heterogeneity into systems of ordinary and discrete differential equations without significantly increasing system dimensionality. The method additionally allows making use of results of bifurcation analysis performed on simplified homogeneous systems, thereby building on the existing body of tools and knowledge and expanding applicability and predictive power of many mathematical models. - Introduces Hidden Keystone Variable (HKV) method, which allows modeling evolution of heterogenous populations, while reducing multi-dimensional selection systems to low-dimensional systems of differential equations - Demonstrates that replicator dynamics is governed by the principle of maximal relative entropy that can be derived from the dynamics of selection systems instead of being postulated - Discusses mechanisms behind models of both Darwinian and non-Darwinian selection - Provides examples of applications to various fields, including cancer growth, global demography, population extinction, tragedy of the commons and resource sustainability, among others - Helps inform differences in underlying mechanisms of population growth from experimental observations, taking one from experiment to theory and back
Dr. Irina Kareva is a theoretical biologist, and the primary focus of her research involves using mathematical modeling to study cancer as an evolving ecosystem within the human body, where heterogeneous populations of cancer cells compete for limited resources (i.e., oxygen and glucose), cooperate with each other to fight off predators (the immune system), and disperse and migrate (metastases). In 2017 Dr. Kareva gave a TED talk on using mathematical modeling for biological research. Dr. Kareva's book Understanding cancer from a systems biology point of view: from observation to theory and back was published by Elsevier in 2018. Dr. Kareva is a Senior Scientist in Simulation and Modeling at EMD Serono, Merck KGaA, where she develops quantitative systems pharmacology (QSP) models to help understand and predict dynamics of new therapeutics.
Dr. Irina Kareva is a theoretical biologist, and the primary focus of her research involves using mathematical modeling to study cancer as an evolving ecosystem within the human body, where heterogeneous populations of cancer cells compete for limited resources (i.e., oxygen and glucose), cooperate with each other to fight off predators (the immune system), and disperse and migrate (metastases). In 2017 Dr. Kareva gave a TED talk on using mathematical modeling for biological research. Dr. Kareva's book Understanding cancer from a systems biology point of view: from observation to theory and back was published by Elsevier in 2018. Dr. Kareva is a Senior Scientist in Simulation and Modeling at EMD Serono, Merck KGaA, where she develops quantitative systems pharmacology (QSP) models to help understand and predict dynamics of new therapeutics.
Autor: | Irina Kareva, Georgy Karev |
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EAN: | 9780128144329 |
eBook Format: | ePUB/PDF |
Sprache: | Englisch |
Produktart: | eBook |
Veröffentlichungsdatum: | 16.10.2019 |
Untertitel: | Theory and Applications |
Kategorie: | |
Schlagworte: | Evolution bifurcation theory cancer cancer modelling differential equations ecology game theory mathematical modelling parameter distribution pre-biological evolution replicator equations strategy selection |
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