TY - JOUR
T1 - Modeling the immune response to HIV infection
AU - Conway, Jessica M.
AU - Ribeiro, Ruy M.
N1 - Funding Information:
This work was supported by the National Science Foundation under Grant No. DMS01714653 (JMC) and by the National Institutes of Health/National Institute of Allergy and Infectious Diseases grant AI104373 (RMR). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Publisher Copyright:
© 2018
PY - 2018/12
Y1 - 2018/12
N2 - The interplay between immune response and HIV is intensely studied via mathematical modeling, with significant insights but few direct answers. In this short review, we highlight advances and knowledge gaps across different aspects of immunity. In particular, we identify the innate immune response and its role in priming the adaptive response as ripe for modeling. The latter have been the focus of most modeling studies, but we also synthesize key outstanding questions regarding effector mechanisms of cellular immunity and development of broadly neutralizing antibodies. Thus far, most modeling studies aimed to infer general immune mechanisms; we foresee that significant progress will be made next by detailed quantitative fitting of models to data, and prediction of immune responses.
AB - The interplay between immune response and HIV is intensely studied via mathematical modeling, with significant insights but few direct answers. In this short review, we highlight advances and knowledge gaps across different aspects of immunity. In particular, we identify the innate immune response and its role in priming the adaptive response as ripe for modeling. The latter have been the focus of most modeling studies, but we also synthesize key outstanding questions regarding effector mechanisms of cellular immunity and development of broadly neutralizing antibodies. Thus far, most modeling studies aimed to infer general immune mechanisms; we foresee that significant progress will be made next by detailed quantitative fitting of models to data, and prediction of immune responses.
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U2 - 10.1016/j.coisb.2018.10.006
DO - 10.1016/j.coisb.2018.10.006
M3 - Review article
C2 - 31463420
AN - SCOPUS:85057202014
SN - 2452-3100
VL - 12
SP - 61
EP - 69
JO - Current Opinion in Systems Biology
JF - Current Opinion in Systems Biology
ER -