A global ”imaging” view on systems approaches in immunology

Ludewig, Burkhard; Stein, Jens V; Sharpe, James; Cervantes-Barragan, Luisa; Thiel, Volker; Bocharov, Gennady (2012). A global ”imaging” view on systems approaches in immunology. European journal of immunology, 42(12), pp. 3116-25. Weinheim: Wiley-VCH 10.1002/eji.201242508

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The immune system exhibits an enormous complexity. High throughput methods such as the "-omic'' technologies generate vast amounts of data that facilitate dissection of immunological processes at ever finer resolution. Using high-resolution data-driven systems analysis, causal relationships between complex molecular processes and particular immunological phenotypes can be constructed. However, processes in tissues, organs, and the organism itself (so-called higher level processes) also control and regulate the molecular (lower level) processes. Reverse systems engineering approaches, which focus on the examination of the structure, dynamics and control of the immune system, can help to understand the construction principles of the immune system. Such integrative mechanistic models can properly describe, explain, and predict the behavior of the immune system in health and disease by combining both higher and lower level processes. Moving from molecular and cellular levels to a multiscale systems understanding requires the development of methodologies that integrate data from different biological levels into multiscale mechanistic models. In particular, 3D imaging techniques and 4D modeling of the spatiotemporal dynamics of immune processes within lymphoid tissues are central for such integrative approaches. Both dynamic and global organ imaging technologies will be instrumental in facilitating comprehensive multiscale systems immunology analyses as discussed in this review.

Item Type:

Journal Article (Original Article)


04 Faculty of Medicine > Pre-clinic Human Medicine > Theodor Kocher Institute

UniBE Contributor:

Stein, Jens Volker








Factscience Import

Date Deposited:

04 Oct 2013 14:36

Last Modified:

20 Feb 2014 01:42

Publisher DOI:


PubMed ID:


Web of Science ID:



https://boris.unibe.ch/id/eprint/14685 (FactScience: 221784)

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