Basic Principles in Modeling Adaptive Regulation and Immunodominance

  • Peter S. KimEmail author
  • Peter P. Lee
  • Doron Levy
Part of the Lecture Notes on Mathematical Modelling in the Life Sciences book series (LMML)


In this chapter we overview our recent work on mathematical models for the regulation of the primary immune response to viral infections and immunodominance. The primary immune response to a viral infection can be very rapid, yet transient. Prior to such a response, potentially reactive T cells wait in lymph nodes until stimulated. Upon stimulation, these cells proliferate for a limited duration and then undergo apoptosis or enter dormancy as memory cells. The mechanisms that trigger the contraction of the T cell population are not well understood. Immunodominance refers to the phenomenon in which simultaneous T cell responses against multiple target epitopes organize themselves into distinct and reproducible hierarchies. In many cases, eliminating the response to the most dominant epitope allows responses to subdominant epitopes to expand more fully. Likewise, if the two most dominant epitopes are removed, then the third most dominant response may expand. The mechanisms that drive immunodominance are also not well understood.


Cell Response Effector Cell Cell Clone Phase Portrait Extended Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was supported in part by the joint NSF/NIGMS program under Grant Number DMS-0758374 and in part by Grant Number R01CA130 817 from the National Cancer Institute. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute or the National Institutes of Health.


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.School of Mathematics and StatisticsUniversity of SydneySydneyAustralia
  2. 2.Division of Hematology, Department of MedicineStanford UniversityStanfordUSA
  3. 3.Department of Mathematics and Center for Scientific Computation and Mathematical Modeling (CSCAMM)University of MarylandCollege ParkUSA

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