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Nonlinear dynamics for biological systems

Record Type:	Electronic resources : Monograph/item
Title/Author:	Nonlinear dynamics for biological systemsedited by Michael Stich, Jorge Carballido-Landeira.
other author:	Stich, Michael.
Published:	Cham :Springer Nature Switzerland :2025.
Description:	xi, 195 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Biological systemsMathematical models.
Online resource:	https://doi.org/10.1007/978-3-031-99044-1
ISBN:	9783031990441$q(electronic bk.)

Nonlinear dynamics for biological systems
Nonlinear dynamics for biological systems[electronic resource] /edited by Michael Stich, Jorge Carballido-Landeira. - Cham :Springer Nature Switzerland :2025. - xi, 195 p. :ill., digital ;24 cm. - SEMA SIMAI Springer series,v. 402199-305X ;. - SEMA SIMAI Springer series ;v.4..

The dynamics of sensorimotor integration -- Unveiling the intrinsic dynamics of biological and artificial neural networks: from criticality to optimal representations -- Emergent complex dynamics in neuronal cultures and its relation to neuroengineering and medicine -- Modeling and analyzing biological systems using branching processes -- Stochastic reaction-diffusion systems in biophysics: towards a toolbox for quantitative model evaluation -- Networks: the visual language of complexity -- Modelling the formation of the granuloma inside secondary lobule of the lungs -- Mathematical model for sustainable biodegradation process.

This book offers a rigorous and fascinating overview of the current state of the art of the application of nonlinear dynamics and closely related methodologies to biological systems. The book has arisen from the presentations and lively discussions at the Third Workshop of Nonlinear Dynamics in Biological Systems, held in Madrid in June 2022, which united world experts analyzing a range of biological and biophysical systems. The chapters in this book describe in a didactic way-but also with the necessary details-abstract and conceptual approaches, as well as numerical, experimental, and data-driven methods. Through these contributions, the nonlinear nature of biological systems is highlighted, as well as the clues for understanding, reproducing, and possibly engineering their complex behavior, hinting occasionally even at their use in medicine. The audience of this book includes, but is not limited to, applied mathematicians, biophysicists, and computational biologists, as well as graduate students in these fields.

ISBN: 9783031990441$q(electronic bk.)

Standard No.: 10.1007/978-3-031-99044-1doiSubjects--Topical Terms:

194442
Biological systems
--Mathematical models.

LC Class. No.: QH323.5

Dewey Class. No.: 570.15118

Nonlinear dynamics for biological systems
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505 0 $a The dynamics of sensorimotor integration -- Unveiling the intrinsic dynamics of biological and artificial neural networks: from criticality to optimal representations -- Emergent complex dynamics in neuronal cultures and its relation to neuroengineering and medicine -- Modeling and analyzing biological systems using branching processes -- Stochastic reaction-diffusion systems in biophysics: towards a toolbox for quantitative model evaluation -- Networks: the visual language of complexity -- Modelling the formation of the granuloma inside secondary lobule of the lungs -- Mathematical model for sustainable biodegradation process.
520 $a This book offers a rigorous and fascinating overview of the current state of the art of the application of nonlinear dynamics and closely related methodologies to biological systems. The book has arisen from the presentations and lively discussions at the Third Workshop of Nonlinear Dynamics in Biological Systems, held in Madrid in June 2022, which united world experts analyzing a range of biological and biophysical systems. The chapters in this book describe in a didactic way-but also with the necessary details-abstract and conceptual approaches, as well as numerical, experimental, and data-driven methods. Through these contributions, the nonlinear nature of biological systems is highlighted, as well as the clues for understanding, reproducing, and possibly engineering their complex behavior, hinting occasionally even at their use in medicine. The audience of this book includes, but is not limited to, applied mathematicians, biophysicists, and computational biologists, as well as graduate students in these fields.
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