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Translational systems biology of inflammation

Vodovotz, Y and Csete, M and Bartels, J and Chang, S and An, G (2008) Translational systems biology of inflammation. PLoS Computational Biology, 4 (4). ISSN 1553-734X

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Inflammation is a complex, multi-scale biologic response to stress that is also required for repair and regeneration after injury. Despite the repository of detailed data about the cellular and molecular processes involved in inflammation, including some understanding of its pathophysiology, little progress has been made in treating the severe inflammatory syndrome of sepsis. To address the gap between basic science knowledge and therapy for sepsis, a community of biologists and physicians is using systems biology approaches in hopes of yielding basic insights into the biology of inflammation. "Systems biology" is a discipline that combines experimental discovery with mathematical modeling to aid in the understanding of the dynamic global organization and function of a biologic system (cell to organ to organism). We propose the term translational systems biology for the application of similar tools and engineering principles to biologic systems with the primary goal of optimizing clinical practice. We describe the efforts to use translational systems biology to develop an integrated framework to gain insight into the problem of acute inflammation. Progress in understanding inflammation using translational systems biology tools highlights the promise of this multidisciplinary field. Future advances in understanding complex medical problems are highly dependent on methodological advances and integration of the computational systems biology community with biologists and clinicians. © 2008 Vodovotz et al.


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Item Type: Article
Status: Published
CreatorsEmailPitt UsernameORCID
Vodovotz, Yvodovotz@pitt.eduVODOVOTZ
Csete, M
Bartels, J
Chang, S
An, G
ContributionContributors NameEmailPitt UsernameORCID
Centers: Other Centers, Institutes, Offices, or Units > McGowan Institute for Regenerative Medicine
Date: 1 April 2008
Date Type: Publication
Journal or Publication Title: PLoS Computational Biology
Volume: 4
Number: 4
DOI or Unique Handle: 10.1371/journal.pcbi.1000014
Schools and Programs: School of Medicine > Immunology
Refereed: Yes
ISSN: 1553-734X
Article Type: Review
PubMed ID: 18437239
Date Deposited: 18 Jul 2012 20:49
Last Modified: 04 Feb 2019 15:58


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