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Review
. 2011:29:527-85.
doi: 10.1146/annurev-immunol-030409-101317.

Systems biology in immunology: a computational modeling perspective

Ronald N Germain  1 , Martin Meier-Schellersheim, Aleksandra Nita-Lazar, Iain D C Fraser
Affiliations
Review

Systems biology in immunology: a computational modeling perspective

Ronald N Germain et al. Annu Rev Immunol. 2011.

Abstract

Systems biology is an emerging discipline that combines high-content, multiplexed measurements with informatic and computational modeling methods to better understand biological function at various scales. Here we present a detailed review of the methods used to create computational models and to conduct simulations of immune function. We provide descriptions of the key data-gathering techniques employed to generate the quantitative and qualitative data required for such modeling and simulation and summarize the progress to date in applying these tools and techniques to questions of immunological interest, including infectious disease. We include comments on what insights modeling can provide that complement information obtained from the more familiar experimental discovery methods used by most investigators and the reasons why quantitative methods are needed to eventually produce a better understanding of immune system operation in health and disease.

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Figure 1
Figure 1
Team approach to modeling. The figure illustrates the various technical, data gathering, and biological components of an integrated research approach to computational systems biology with a focus on fine-grained, dynamic modeling and simulation of processes such as cell signaling.
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