Systems immunology: Integrating multi-omics data to infer regulatory networks and hidden drivers of immunity. Issue 15 (June 2019)

• Record Type: Journal Article
• Authors: Yu, Jiyang; Peng, Junmin; Chi, Hongbo
• Is Part Of: Current opinion in systems biology. Issue 15(2019)
• Page Start: 19
• Page End: 29
• Publication Date: 2019-06
• Subjects: Cell–cell communication -- Gene regulatory network -- Hidden driver analysis -- Systems immunology -- scRNA-seq; ChIP-seq chromatin immunoprecipitation sequencing -- CLIP-seq crosslinking immunoprecipitation sequencing -- BS-seq bisulfite sequencing -- ATAC-seq assay for transposase-accessible chromatin using sequencing -- Hi-C all-vs-all chromosome conformation capture by sequencing -- CyTOF cytometry by time of flight -- LC–MS liquid chromatography–mass spectrometry -- CRISPR clustered regularly interspaced short palindromic repeats -- Cas CRISPR associated protein -- RNAi RNA interference -- FACS fluorescence activated cell sorting -- SC3 single-cell consensus clutering -- WGCNA weighted gene coexpression network analysis -- CAR chimeric antigen receptor -- smFISH single molecule fluorescence in situ hybridization -- NetBID data-driven network-based Bayesian inference of drivers; Systems biology -- Periodicals; 570
• DOI: 10.1016/j.coisb.2019.03.003
• Languages: English
• ISSNs: 2452-3100

Abstract

Abstract: The immune system is a highly complex and dynamic biological system. It operates through intracellular molecular networks and intercellular (cell–cell) interaction networks. Systems immunology is an emerging discipline that applies systems biology approaches of integrating high-throughput multi-omics measurements with computational network modeling to better understand immunity at various scales. In this review, we summarize key omics technologies and computational approaches used for immunological studies at both population and single-cell levels. We highlight the hidden driver analysis based on data-driven networks and comment on the potential of translating systems immunology discoveries to immunotherapy of cancer and other human diseases. Graphical abstract: Image 1 Highlights: Systems immunology is emerging with omics tools at population and single-cell levels. Integrative analysis of multi-omics data has revealed novel insights into immunology. Single-cell sequencing technology is driving immunology research. Data-driven and context-specific networks enable capture of hidden drivers.