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Record Nr. |
UNINA9910254617703321 |
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Autore |
Ashcroft Peter |
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Titolo |
The Statistical Physics of Fixation and Equilibration in Individual-Based Models / / by Peter Ashcroft |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
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ISBN |
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Edizione |
[1st ed. 2016.] |
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Descrizione fisica |
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1 online resource (XV, 164 p. 63 illus., 13 illus. in color.) |
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Collana |
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Springer Theses, Recognizing Outstanding Ph.D. Research, , 2190-5053 |
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Disciplina |
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Soggetti |
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Sociophysics |
Econophysics |
Biomathematics |
Bioinformatics |
Probabilities |
Game theory |
Cancer - Research |
Data-driven Science, Modeling and Theory Building |
Mathematical and Computational Biology |
Probability Theory and Stochastic Processes |
Game Theory, Economics, Social and Behav. Sciences |
Cancer Research |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references at the end of each chapters. |
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Nota di contenuto |
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Introduction -- Technical Background -- Finite Populations in Switching Environments -- Fixation Time Distribution -- Metastable States in Cancer Initiation -- The WKB Method: A User-guide -- Conclusions. |
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Sommario/riassunto |
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This thesis explores several interdisciplinary topics at the border of theoretical physics and biology, presenting results that demonstrate the power of methods from statistical physics when applied to neighbouring disciplines. From birth-death processes in switching environments to discussions on the meaning of quasi-potential |
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landscapes in high-dimensional spaces, this thesis is a shining example of the efficacy of interdisciplinary research. The fields advanced in this work include game theory, the dynamics of cancer, and invasion of mutants in resident populations, as well as general contributions to the theory of stochastic processes. The background material provides an intuitive introduction to the theory and applications of stochastic population dynamics, and the use of techniques from statistical physics in their analysis. The thesis then builds on these foundations to address problems motivated by biological phenomena. |
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