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Killer Cell Dynamics Mathematical and Computational Approaches to Immunology /
This book reviews how mathematics can be used in combination with biological data in order to improve understanding of how the immune system works. This is illustrated largely in the context of viral infections. Mathematical models allow scientists to capture complex biological interactions in a cle...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York, NY :
Springer New York : Imprint: Springer,
2007.
|
| Edición: | 1st ed. 2007. |
| Colección: | Interdisciplinary Applied Mathematics,
32 |
| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 024 | 7 | |a 10.1007/978-0-387-68733-9 |2 doi | |
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| 082 | 0 | 4 | |a 570.285 |2 23 |
| 100 | 1 | |a Wodarz, Dominik. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Killer Cell Dynamics |h [electronic resource] : |b Mathematical and Computational Approaches to Immunology / |c by Dominik Wodarz. |
| 250 | |a 1st ed. 2007. | ||
| 264 | 1 | |a New York, NY : |b Springer New York : |b Imprint: Springer, |c 2007. | |
| 300 | |a XIII, 220 p. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 490 | 1 | |a Interdisciplinary Applied Mathematics, |x 2196-9973 ; |v 32 | |
| 505 | 0 | |a Viruses and Immune Responses: A Dynamical View -- Models of CTL Responses and Correlates of Virus Control -- CTL Memory -- CD4 T Cell Help -- Immunodominance -- Multiple Infections and CTL Dynamics -- Control versus CTL-Induced Pathology -- Lytic versus Nonlytic Activity -- Dynamical Interactions between CTL and Antibody Responses -- Effector Molecules and CTL Homeostasis -- Virus-Induced Subversion of CTL Responses -- Boosting Immunity against Immunosuppressive Infections -- Evolutionary Aspects of Immunity. | |
| 520 | |a This book reviews how mathematics can be used in combination with biological data in order to improve understanding of how the immune system works. This is illustrated largely in the context of viral infections. Mathematical models allow scientists to capture complex biological interactions in a clear mathematical language and to follow them to their precise logical conclusions. This can give rise to counter-intuitive insights which would not be attained by experiments alone, and can be used for the design of further experiments in order to address the mathematical results. This book provides both an introduction to the field of mathematical immunology, and an overview of many topics which are the subject of current research, covering a broad variety of immunological topics. It starts with basic principles of immunology and covers the dynamical interactions between the immune system and specific viral infections, including important human pathogens such as HIV. General biological and mathematical background material to both virus infection and immune system dynamics is provided, and each chapter begins with a simple introduction to the biological questions examined. This book is intended for an interdisciplinary audience. It explains the concept of mathematical modeling in immunology and shows how modeling has been used to address specific questions. It is intended both for the mathematical biologists who are interested in immunology, and for the biological readership that is interested in the use of mathematical models in immunology. Dominik Wodarz is an Associate Professor at the Department of Ecology and Evolutionary Biology at the University of California, Irvine. | ||
| 650 | 0 | |a Biomathematics. | |
| 650 | 0 | |a Immunology. | |
| 650 | 0 | |a Ecology . | |
| 650 | 0 | |a Evolution (Biology). | |
| 650 | 0 | |a Cytology. | |
| 650 | 1 | 4 | |a Mathematical and Computational Biology. |
| 650 | 2 | 4 | |a Immunology. |
| 650 | 2 | 4 | |a Ecology. |
| 650 | 2 | 4 | |a Theoretical and Statistical Ecology. |
| 650 | 2 | 4 | |a Evolutionary Biology. |
| 650 | 2 | 4 | |a Cell Biology. |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9781441921659 |
| 776 | 0 | 8 | |i Printed edition: |z 9780387511511 |
| 776 | 0 | 8 | |i Printed edition: |z 9780387308937 |
| 830 | 0 | |a Interdisciplinary Applied Mathematics, |x 2196-9973 ; |v 32 | |
| 856 | 4 | 0 | |u https://doi.uam.elogim.com/10.1007/978-0-387-68733-9 |z Texto Completo |
| 912 | |a ZDB-2-SMA | ||
| 912 | |a ZDB-2-SXMS | ||
| 950 | |a Mathematics and Statistics (SpringerNature-11649) | ||
| 950 | |a Mathematics and Statistics (R0) (SpringerNature-43713) | ||