title: Computational approaches to understanding dendritic cell responses to influenza virus infection.
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/                                    .
authors.affiliation: Department of Neurology and Center for Translational Systems Biology, Mount Sinai School of Medicine, One Gustave L. Levy Place, New York, NY 10029-6574, USA.
authors.forename: Elena
authors.initials: E
authors.lastname: Zaslavsky
authors.forename: Fernand
authors.initials: F
authors.lastname: Hayot
authors.forename: Stuart C
authors.initials: SC
authors.lastname: Sealfon
mesh_terms: D019295:Computational Biology / Q000379:methods*; D003713:Dendritic Cells / Q000276:immunology*; D006801:Humans; D055633:Immune System Phenomena; D007251:Influenza, Human / Q000276:immunology* / Q000821:virology; D008954:Models, Biological; D009975:Orthomyxoviridae