Virus Dynamics : Mathematical Principles of Immunology and Virology: Mathematical Principles of Immunology and VirologyThis groundbreaking book describes the emerging field of theoretical immunology, in particular the use of mathematical models to describe the spread of infectious diseases within patients. It reveals fascinating insights into the dynamics of viral and other infections, and the interactions between infectious agents and immune responses. Structured around the examples of HIV/AIDS and hepatitis B, Nowak and May show how mathematical models can help researchers to understand the detailed dynamics of infection and the effects of antiviral therapy. Models are developed to describe the dynamics of drug resistance, immune responses, viral evolution and mutation, and to optimise the design of therapy and vaccines. - ;We know, down to the tiniest details, the molecular structure of the human immunodeficiency virus (HIV). Yet despite this tremendous accomplishment, and despite other remarkable advances in our understanding of individual viruses and cells of the immune system, we still have no agreed understanding of the ultimate course and variability of the pathogenesis of AIDS. Gaps in our understanding like these impede our efforts towards developing effective therapies and preventive vaccines. Martin Nowak and Robert M May describe the emerging field of theoretical immunology in this accessible and well- written text. Using mathematical modelling techniques, the authors set out their ideas about how populations of viruses and populations of immune system cells may interact in various circumstances, and how infectious diseases spread within patients. They explain how this approach to understanding infectious diseases can reveal insights into the dynamics of viral and other infections, and the interactions between infectious agents and immune responses. The book is structured around the examples of HIV/AIDS and Hepatitis B virus, although the approaches described will be more widely applicable. The authors use mathematical tools to uncover the detailed dynamics of the infection and the effects of antiviral therapy. Models are developed to describe the emergence of drug resistance, and the dynamics of immune responses, viral evolution, and mutation. The practical implications of this work for optimisation of the design of therapy and vaccines are discussed. The book concludes with a glance towards the future of this fascinating, and potentially highly useful, field of study. - ;... an excellent introduction to a field that has the potential to advance substantially our understanding of the complex interplay between virus and host - Nature |
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Contents
I | 2 |
II | 4 |
III | 5 |
IV | 7 |
V | 10 |
VI | 11 |
VII | 12 |
VIII | 14 |
LXIV | 90 |
LXV | 91 |
LXVII | 92 |
LXVIII | 93 |
LXIX | 94 |
LXX | 96 |
LXXI | 97 |
LXXII | 98 |
IX | 15 |
X | 16 |
XI | 17 |
XII | 18 |
XIII | 19 |
XIV | 22 |
XVI | 25 |
XVII | 26 |
XVIII | 27 |
XIX | 28 |
XX | 31 |
XXI | 33 |
XXII | 35 |
XXIV | 37 |
XXV | 39 |
XXVI | 40 |
XXVII | 41 |
XXVIII | 42 |
XXIX | 43 |
XXX | 44 |
XXXI | 45 |
XXXIII | 46 |
XXXIV | 47 |
XXXV | 51 |
XXXVI | 52 |
XXXVII | 53 |
XXXIX | 54 |
XL | 56 |
XLI | 57 |
XLIII | 59 |
XLIV | 60 |
XLV | 62 |
XLVI | 64 |
XLVII | 67 |
XLVIII | 68 |
XLIX | 70 |
L | 72 |
LI | 75 |
LII | 76 |
LIII | 77 |
LIV | 78 |
LV | 81 |
LVI | 82 |
LVII | 83 |
LVIII | 84 |
LIX | 85 |
LX | 86 |
LXI | 87 |
LXII | 88 |
LXIII | 89 |
LXXIV | 101 |
LXXV | 102 |
LXXVI | 103 |
LXXVII | 104 |
LXXVIII | 106 |
LXXIX | 109 |
LXXX | 110 |
LXXXI | 111 |
LXXXIV | 117 |
LXXXV | 122 |
LXXXVI | 124 |
LXXXVII | 126 |
LXXXVIII | 130 |
LXXXIX | 134 |
XC | 137 |
XCI | 138 |
XCIII | 139 |
XCIV | 143 |
XCV | 144 |
XCVI | 147 |
XCVII | 148 |
XCVIII | 149 |
XCIX | 150 |
C | 154 |
CI | 156 |
CII | 158 |
CIII | 162 |
CIV | 163 |
CV | 164 |
CVI | 165 |
CVII | 168 |
CVIII | 170 |
CIX | 175 |
CXI | 176 |
CXII | 178 |
CXIII | 180 |
CXIV | 182 |
CXV | 183 |
CXVI | 187 |
CXVII | 188 |
CXIX | 189 |
CXXI | 197 |
CXXIII | 198 |
CXXIV | 201 |
CXXV | 203 |
CXXVI | 205 |
CXXVII | 208 |
210 | |
234 | |
Other editions - View all
Virus Dynamics: Mathematical Principles of Immunology and Virology Martin Nowak,Robert M. May No preview available - 2000 |
Virus Dynamics: Mathematical Principles of Immunology and Virology Martin Nowak,Robert M. May No preview available - 2000 |
Common terms and phrases
abundance of uninfected anti-viral antibody antigenic diversity antigenic variation assume average basic model basic reproductive ratio converge cross-reactive immune response CTL response CTL-mediated lysis cytopathic death rate denotes disease progression diversity threshold drug treatment epitope equations equilibrium equilibrium abundance equilibrium virus load exponential exponential decay fixed point frequency genome half-life HIV infection immune responses immune system immunodominance immunogenic increase infected cells infected patients infected PBMC initial killing lamivudine latently infected cells lentivirus mathematical models model of virus molecules mutant virus mutation rate Nowak oscillations PBMC Perelson plasma virus load produced productively infected cells protein provirus quasispecies rate of CTL-mediated rate of infected replication rates resistant mutant resistant virus reverse transcriptase inhibitor saturated sequence stimulation strain-specific immune responses T-cell target cells therapy viral virions virus decline virus dynamics virus load virus mutants virus population viruses wild-type virus zidovudine
Popular passages
Page 230 - Shankarappa, R., Margolick, JB, Gange, SJ, Rodrigo, AG, Upchurch, D., Farzadegan, H., Gupta, P., Rinaldo, CR, Learn, GH, He, X., Huang, X.-L.
Page 210 - Rapid development of isolate-specific neutralizing antibodies after primary HIV-1 infection and consequent emergence of virus variants which resist neutralization by autologous sera.
Page 224 - Quantitation of HIV-1 RNA in plasma predicts outcome after seroconversion. Ann Intern Med 1995; 122:573-9.
Page 230 - O'Hara, CJ, Groopman, JE, Cho, E.-S., Oleske, JM, Wong-Staal, E, Gallo, RC (1985) HTLV-III infection in brains of children and adults with AIDS encephalopathy.
Page 228 - JD (1993) High levels of HIV-1 in plasma during all stages of infection determined by competitive PCR.
Page 210 - LH (1989). Ordered appearance of antigenic variants of African trypanosomes explained in a mathematical model based on a stochastic switch process and immune-selection against putative switch intermediates. Proc.
Page 221 - Lifson, JD, Feinberg, MB, Reyes, GR, Rabin, L., Banapour, B., Chakrabarti, S., Moss, B., Wong-Staal, F. Steimer, KS and Engleman, EG (1986/?). Induction of CD4-dependent cell fusion by the HTLV-III/LAV envelope.
Page 219 - Dramatic rise in plasma viremia after CD8(+) T cell depletion in simian immunodeficiency virus-infected macaques. J. Exp. Med..
Page 224 - Meyerhans. A., Cheynier, R.. Albert, J., Seth, M., Kwok. S., Sninsky, J., Morfeldt-Manson, L., Asjo, B., WainHobson, S.