Immunologic Research

, Volume 54, Issue 1, pp 160–168

Computational approaches to understanding dendritic cell responses to influenza virus infection

  • Elena Zaslavsky
  • Fernand Hayot
  • Stuart C. Sealfon
Immunology at Mount Sinai

DOI: 10.1007/s12026-012-8322-6

Cite this article as:
Zaslavsky, E., Hayot, F. & Sealfon, S.C. Immunol Res (2012) 54: 160. doi:10.1007/s12026-012-8322-6
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Abstract

The evolution of immunology research from measurements of single entities to large-scale data-intensive assays necessitates the integration of experimental work with bioinformatics and computational approaches. The introduction of physics into immunology has led to the study of new phenomena, such as cellular noise, which is likely to prove increasingly important to understand immune system responses. The fusion of “hard science” and biology is also leading to a re-examination of data acquisition, analysis, and statistical validation and is resulting in the development of easy-to-access tools for immunology research. Here, we review some of our models, computational tools, and results related to studies of the innate immune response of human dendritic cells to viral infection. Our project functions on an open model across institutions with electronic record keeping and public sharing of data. Our tools, models, and data can be accessed at http://tsb.mssm.edu/primeportal/.

Keywords

Computational immunologyToolsModelsDendritic cells

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Elena Zaslavsky
    • 1
  • Fernand Hayot
    • 1
  • Stuart C. Sealfon
    • 1
  1. 1.Department of Neurology and Center for Translational Systems BiologyMount Sinai School of MedicineNew YorkUSA