Mathematics for Life Science and Medicine
Dynamical systems theory in mathematical biology has attracted much attention from many scientific directions. The purpose of this volume is to present and discuss the many rich properties of the dynamical systems that appear in life science and medicine. The main topics include cancer treatment, dy...
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Auteurs principaux : | , , |
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Collectivité auteur : | |
Format : | Livre |
Langue : | anglais |
Titre complet : | Mathematics for Life Science and Medicine / Yasuhiro Takeuchi, Yoh Iwasa, Kazunori Sato (Eds.) |
Publié : |
Berlin, Heidelberg :
Springer Berlin Heidelberg
, 2007 Cham : Springer Nature |
Collection : | Biological and medical physics, biomedical engineering (Internet) |
Accès en ligne : |
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Condition d'utilisation et de reproduction : | Conditions particulières de réutilisation pour les bénéficiaires des licences nationales : chttps://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 |
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Documents associés : | Autre format:
Mathematics for Life Science and Medicine Autre format: Mathematics for Life Science and Medicine Autre format: Mathematics for Life Science and Medicine |
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330 | |a Dynamical systems theory in mathematical biology has attracted much attention from many scientific directions. The purpose of this volume is to present and discuss the many rich properties of the dynamical systems that appear in life science and medicine. The main topics include cancer treatment, dynamics of paroxysmal tachycardia, vector disease models, epidemic diseases and metapopulations, immune systems, pathogen competition and coexistence and the evolution of virulence and the rapid evolution of viruses within a host. Each chapter will serve to introduce students and scholars to the state-of-the-art in an exciting area, to present new results, and to inspire future contributions to mathematical modeling in life science and medicine. | ||
359 | 1 | |a Mathematical Studies of Dynamics and Evolution of Infectious Diseases -- Basic Knowledge and Developing Tendencies in Epidemic Dynamics -- Delayed SIR Epidemic Models for Vector Diseases? -- Epidemic Models with Population Dispersal -- Spatial-Temporal Dynamics in Nonlocal Epidemiological Models -- Pathogen Competition and Coexistence and the Evolution of Virulence -- Directional Evolution of Virus Within a Host Under Immune Selection -- Stability Analysis of a Mathematical Model of the Immune Response with Delays -- Modeling Cancer Treatment Using Competition: A Survey. | |
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