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Mathematical Modeling for the Life Sciences [electronic resource] / by Jacques Istas.

Por: Tipo de material: TextoTextoSeries Universitext | UniversitextEditor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2005Descripción: VIII, 168 p. 2 illus. online resourceTipo de contenido:
  • text
Tipo de medio:
  • computer
Tipo de soporte:
  • online resource
ISBN:
  • 9783540278771
Trabajos contenidos:
  • SpringerLink (Online service)
Tema(s): Formatos físicos adicionales: Sin títuloClasificación CDD:
  • 519 23
Clasificación LoC:
  • T57-57.97
Recursos en línea:
Contenidos:
Springer eBooksResumen: Proposing a wide range of mathematical models that are currently used in life sciences may be regarded as a challenge, and that is precisely the challenge that this book takes up. Of course this panoramic study does not claim to offer a detailed and exhaustive view of the many interactions between mathematical models and life sciences. This textbook provides a general overview of realistic mathematical models in life sciences, considering both deterministic and stochastic models and covering dynamical systems, game theory, stochastic processes and statistical methods. Each mathematical model is explained and illustrated individually with an appropriate biological example. Finally three appendices on ordinary differential equations, evolution equations, and probability are added to make it possible to read this book independently of other literature.
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General introduction -- Continuous-time dynamical systems -- Discrete-time dynamical systems -- Game theory and evolution -- Markov chains and diffusions -- Random arborescent models -- Statistics.

Proposing a wide range of mathematical models that are currently used in life sciences may be regarded as a challenge, and that is precisely the challenge that this book takes up. Of course this panoramic study does not claim to offer a detailed and exhaustive view of the many interactions between mathematical models and life sciences. This textbook provides a general overview of realistic mathematical models in life sciences, considering both deterministic and stochastic models and covering dynamical systems, game theory, stochastic processes and statistical methods. Each mathematical model is explained and illustrated individually with an appropriate biological example. Finally three appendices on ordinary differential equations, evolution equations, and probability are added to make it possible to read this book independently of other literature.

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