Nonlinear Dynamics for Biological Systems Nonlinear Dynamics for Biological Systems
SEMA SIMAI Springer Series

Nonlinear Dynamics for Biological Systems

    • ‏119٫99 US$
    • ‏119٫99 US$

وصف الناشر

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.

النوع
علم وطبيعة
تاريخ النشر
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١٢ أكتوبر
اللغة
EN
الإنجليزية
عدد الصفحات
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الناشر
Springer Nature Switzerland
البائع
Springer Nature B.V.
الحجم
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‫م.ب.‬
Mathematical and Computational Modelling, Approximation and Simulation Mathematical and Computational Modelling, Approximation and Simulation
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New Challenges for Cancer Systems Biomedicine New Challenges for Cancer Systems Biomedicine
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Computing Qualitatively Correct Approximations of Balance Laws Computing Qualitatively Correct Approximations of Balance Laws
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Advances in Numerical Simulation in Physics and Engineering Advances in Numerical Simulation in Physics and Engineering
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Advances in Differential Equations and Applications Advances in Differential Equations and Applications
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New Challenges in Grid Generation and Adaptivity for Scientific Computing New Challenges in Grid Generation and Adaptivity for Scientific Computing
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