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General information

URL: http://bioinfo.life.hust.edu.cn/EVAtlas
Full name: Extracellular Vesicles Atlas
Description: Extracellular Vesicle Atlas (EVAtlas) is an update of EVmiRNA database. We performed a unified read dynamic assignment algorithm (RDAA) considering mismatch and multi-mapping reads to quantify the expression profiles of seven ncRNA types (miRNA, snoRNA, piRNA, snRNA, rRNA, tRNA and Y RNA).
Year founded: 2019
Last update: 2021
Version:
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Country/Region: China

Contact information

University/Institution: Huazhong University of Science and Technology
Address: Department of Bioinformatics and Systems Biology. College of Life Science and Technology Huazhong University of Science and Technology, Wuhan 430074 P.R. China
City: Wuhan
Province/State: Hubei
Country/Region: China
Contact name (PI/Team): Anyuan Guo
Contact email (PI/Helpdesk): guoay@hust.edu.cn

Publications

34387689
EVAtlas: a comprehensive database for ncRNA expression in human extracellular vesicles. [PMID: 34387689]
Liu CJ, Xie GY, Miao YR, Xia M, Wang Y, Lei Q, Zhang Q, Guo AY.

Extracellular vesicles (EVs) packing various molecules play vital roles in intercellular communication. Non-coding RNAs (ncRNAs) are important functional molecules and biomarkers in EVs. A comprehensive investigation of ncRNAs expression in EVs under different conditions is a fundamental step for functional discovery and application of EVs. Here, we curated 2030 small RNA-seq datasets for human EVs (1506 sEV and 524 lEV) in 24 conditions and over 40 diseases. We performed a unified reads dynamic assignment algorithm (RDAA) considering mismatch and multi-mapping reads to quantify the expression profiles of seven ncRNA types (miRNA, snoRNA, piRNA, snRNA, rRNA, tRNA and Y RNA). We constructed EVAtlas (http://bioinfo.life.hust.edu.cn/EVAtlas), a comprehensive database for ncRNA expression in EVs with four functional modules: (i) browse and compare the distribution of ncRNAs in EVs from 24 conditions and eight sources (plasma, serum, saliva, urine, sperm, breast milk, primary cell and cell line); (ii) prioritize candidate ncRNAs in condition related tissues based on their expression; (iii) explore the specifically expressed ncRNAs in EVs from 24 conditions; (iv) investigate ncRNA functions, related drugs, target genes and EVs isolation methods. EVAtlas contains the most comprehensive ncRNA expression in EVs and will be a key resource in this field.

Nucleic Acids Res. 2021:() | 24 Citations (from Europe PMC, 2024-11-16)
30335161
EVmiRNA: a database of miRNA profiling in extracellular vesicles. [PMID: 30335161]
Liu T, Zhang Q, Zhang J, Li C, Miao YR, Lei Q, Li Q, Guo AY.

Extracellular vesicles (EVs), such as exosomes and microvesicles, acted as cell-to-cell communication vectors and potential biomarkers for diseases. microRNAs (miRNAs) are the most well studied molecules in EVs, thus a comprehensive investigation of miRNA expression profiles in EVs will be helpful to explore their functions and biomarkers. We curated 462 small RNA sequencing samples of EVs from 17 sources/diseases and constructed the EVmiRNA database (http://bioinfo.life.hust.edu.cn/EVmiRNA) to show the miRNA expression profiles. We found >1000 miRNAs expressed in these EVs and detected specific miRNAs for EVs of each source/disease. EVmiRNA provides three functional modules: (i) the miRNA expression profiles and the sample information of EVs from different sources (such as blood, breast milk etc.); (ii) the specifically expressed miRNAs in different EVs that would be helpful for biomarker identification; (iii) the miRNA annotations including the miRNA expression in EVs and TCGA cancer types, miRNA pathway regulations as well as miRNA function and publications. EVmiRNA has a user-friendly web interface with powerful browse and search functions, as well as data downloading. It is the first database focusing on miRNA expression profiles in EVs and will be useful for the research and application community of EV biomarker, miRNA function and liquid biopsy.

Nucleic Acids Res. 2019:47(D1) | 145 Citations (from Europe PMC, 2024-11-16)

Ranking

All databases:
381/6265 (93.935%)
Expression:
59/1209 (95.203%)
Pathway:
28/411 (93.431%)
381
Total Rank
156
Citations
31.2
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Record metadata

Created on: 2019-01-04
Curated by:
Yuxin Qin [2022-05-11]
Dong Zou [2019-01-11]
Dong Zou [2019-01-04]