ArticleNucleic acids research2026
EVmiRNA2.0: an updated database for miRNA expression in comprehensive human extracellular vesicles.
Article in Nucleic acids research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Pathophysiological and Molecular Features of DXd ADC-Related Interstitial Pneumonitis in Cynomolgus Monkeys.Cancer science · 2026Article
- circ_0044235 exacerbates neuroinflammation and apoptosis following spinal cord injury by targeting miR-338-5p.Journal of orthopaedic surgery and research · 2026Article
- Quantification of EV-associated miRNA in liquid biopsies for biomarker signature development.Extracellular vesicles and circulating nucleic acids · 2026Review
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Authors and funding
6 authors.
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Abstract
Extracellular vesicle (EV)-derived microRNAs (miRNAs) are critical mediators of intercellular communication and play important roles in diverse physiological and pathological processes. However, existing EV miRNA databases are limited by outdated datasets, narrow sample diversity, and the absence of integrated analytical functions. Here, we present EVmiRNA2.0, a substantially updated database for miRNA expression in human EVs. EVmiRNA2.0 integrates 7254 human EV small RNA sequencing (smRNA-seq) samples from 45 distinct sources and 143 disease types. Compared with the previous version, EVmiRNA2.0 has the following key improvements: (i) a substantial increase in EVs datasets, expanding from 462 to 7254, a 15-fold augmentation in data volume; (ii) a flexible online differential expression analysis module, allowing users to filter and compare samples based on a project, EV subtype, sample source, and disease stage/treatment; (iii) an enhanced miRNA search system featuring cross-tissue, cross-fluid, and cross-cell-type expression profiles, along with curated functional annotation, predicted target genes, and drug interaction data; (iv) useful download options for both raw expression data and analysis results. With comprehensive datasets and improved functions, EVmiRNA2.0 will serve as a useful and indispensable resource for exploring the expression and function of EV-derived miRNAs. It is freely accessible at https://guolab.wchscu.cn/EVmiRNA2.0/.
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Registered trials
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