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Extracellular vesicles (EVs) are membrane-enclosed structures secreted by cells. In the past decade, EVs have attracted substantial attention as carriers of complex intercellular information. They have been implicated in a wide variety of biological processes in health and disease. They are also considered to hold promise for future diagnostics and therapy. EVs are characterized by a previously underappreciated heterogeneity. The heterogeneity and molecular complexity of EVs necessitates high-throughput analytical platforms for detailed analysis. Recently, mass spectrometry, next-generation sequencing and bioinformatics tools have enabled detailed proteomic, transcriptomic, glycomic, lipidomic, metabolomic, and genomic analyses of EVs. Here, we provide an overview of systems biology experiments performed in the field of EVs. Furthermore, we provide examples of how in silico systems biology approaches can be used to identify correlations between genes involved in EV biogenesis and human diseases. Using a knowledge fusion system, we investigated whether certain groups of proteins implicated in the biogenesis/release of EVs were associated with diseases and phenotypes. Furthermore, we investigated whether these proteins were enriched in publicly available transcriptomic datasets using gene set enrichment analysis methods. We found associations between key EV biogenesis proteins and numerous diseases, which further emphasizes the key role of EVs in human health and disease.
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