| Literature DB >> 32060427 |
Manon Eckhardt1,2,3, Judd F Hultquist4,5,6,7, Robyn M Kaake1,2,3, Ruth Hüttenhain1,2,3, Nevan J Krogan8,9,10.
Abstract
Ongoing social, political and ecological changes in the 21st century have placed more people at risk of life-threatening acute and chronic infections than ever before. The development of new diagnostic, prophylactic, therapeutic and curative strategies is critical to address this burden but is predicated on a detailed understanding of the immensely complex relationship between pathogens and their hosts. Traditional, reductionist approaches to investigate this dynamic often lack the scale and/or scope to faithfully model the dual and co-dependent nature of this relationship, limiting the success of translational efforts. With recent advances in large-scale, quantitative omics methods as well as in integrative analytical strategies, systems biology approaches for the study of infectious disease are quickly forming a new paradigm for how we understand and model host-pathogen relationships for translational applications. Here, we delineate a framework for a systems biology approach to infectious disease in three parts: discovery - the design, collection and analysis of omics data; representation - the iterative modelling, integration and visualization of complex data sets; and application - the interpretation and hypothesis-based inquiry towards translational outcomes.Entities:
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Year: 2020 PMID： 32060427 PMCID： PMC7839161 DOI： 10.1038/s41576-020-0212-5
Source DB: PubMed Journal: Nat Rev Genet ISSN： 1471-0056 Impact factor: 53.242