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.

Résumé
Systems biology and computational biology have recently become prominent areas of research in the biomedical community, especially in the area of cell biology. Given that much information on genes and their protein products has become available, the big question is how the individual components interact and work together, and how this determines the functioning of cells, organs, and organisms. Long before the popularity of systems biology in biomedicine, however, such approaches have been used successfully in a di?erent area of biology: population ecology. Research in the area of population dynamics - vestigated complex interactions between di?erent populations of organisms, such as the dynamics of competition and predation, food webs, community structure, as well as the epidemiology of infectious diseases. In this ?eld, t- oretical biology and mathematical modeling have become an integral part of research. Mathematical models allowed people to obtain interesting and counter-intuitive insights into how complex interactions among di?erent p- ulations can play out. Such mathematical studies not only gave rise to - teresting theoretical ideas, but also provided the basis for the design of new experimental work and de?ned major questions and directions of research. Around 1990, such population dynamic concepts, and the use of mathema- cal/computational approaches, started to be applied to the in vivo dynamics between viruses and the immune system. These interactions have many s- ilarities to ecological, epidemiological, and evolutionary principles. Consider theepidemiologicalspreadofapathogen(suchasthecommoncold)througha population of hosts.

Contenu
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.