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. 2020 Nov 13;21(22):8550. doi: 10.3390/ijms21228550

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© 2020 by the authors.

Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

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Correlation between EVs content in RNA, protein, lipid, and metabolites types and the multiple omics analyses that EV data integration can generate. Several areas of biology and medical research (input) generate complex genomics, transcriptomics, proteomics, lipidomics, and metabolomics analysis that can contribute to understanding several biological processes and functions (output). By means of bioinformatics tools, these data will be preprocessed and then integrated in order to answer various biological questions regarding intercellular communication (A). General structure of an EV, with specific EV markers—CD9, CD63, CD80, CD81, flotillin 1, Alix, and TSG101 (B). Figure created with BioRender.com.