Monograph

Finite-Size Effects in Stochastic Models of Population Dynamics: Applications to Biomedicine and Biology

  • Francesca Di Patti,

Population dynamics constitutes a widespread branch of investigations which finds important applications within the realm of life science. The classical deterministic (macroscopic) approach aims at characterizing the time evolution of families of homologous entities, so to unravel the global mechanisms which drive their dynamics. As opposed to this formulation, a microscopic level of modeling can be invoked which instead focuses on the explicit rules governing the interactions among individuals. A viable tool that enables to bridge the gap between the two approaches is the van Kampen's system size expansion. In this thesis we use this method to show how the finite-size effects accounted by the microscopic level might significantly alter the dynamics of biological phenomena.

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Francesca Di Patti

University of Florence, Italy - ORCID: 0000-0003-1288-0079

Francesca Di Patti received her Ph.D. in Nonlinear Dynamics and Complex Systems from the University of Florence where she also obtained her Master's degree in Mathematics. Currently she is post-doc researcher at the Physics Department of the University of Padua.
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  • Publication Year: 2010
  • Pages: 126
  • eISBN: 978-88-8453-917-5
  • Content License: CC BY-ND 3.0 IT
  • © 2010 Author(s)

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  • Publication Year: 2010
  • eISBN: 978-88-9273-690-0
  • Content License: CC BY-ND 3.0 IT
  • © 2010 Author(s)

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  • Publication Year: 2010
  • Pages: 126
  • eISBN: 978-88-8453-976-2
  • Content License: CC BY-ND 3.0 IT
  • © 2010 Author(s)

Bibliographic Information

Book Title

Finite-Size Effects in Stochastic Models of Population Dynamics: Applications to Biomedicine and Biology

Authors

Francesca Di Patti

Peer Reviewed

Number of Pages

126

Publication Year

2010

Copyright Information

© 2010 Author(s)

Content License

CC BY-ND 3.0 IT

Metadata License

CC0 1.0

Publisher Name

Firenze University Press

DOI

10.36253/978-88-8453-917-5

ISBN Print

978-88-8453-976-2

eISBN (pdf)

978-88-8453-917-5

eISBN (xml)

978-88-9273-690-0

Series Title

Premio Tesi di Dottorato

Series Issn ISSN

2612-8039

Series E-Issn

2612-8020

247

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