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ExomiRHub: A comprehensive database for hosting and analyzing human disease-related extracellular microRNA transcriptomics data

Authors :
Yang Liu
Zhuochao Min
Jing Mo
Zhen Ju
Jianliang Chen
Weiling Liang
Lantian Zhang
Hanguang Li
Godfrey Chi-Fung Chan
Yanjie Wei
Wenliang Zhang
Source :
Computational and Structural Biotechnology Journal, Vol 23, Iss , Pp 3104-3116 (2024)
Publication Year :
2024
Publisher :
Elsevier, 2024.

Abstract

Extracellular microRNA (miRNA) expression data generated by different laboratories exhibit heterogeneity, which poses challenges for biologists without bioinformatics expertise. To address this, we introduce ExomiRHub (http://www.biomedical-web.com/exomirhub/), a user-friendly database designed for biologists. This database incorporates 191 human extracellular miRNA expression datasets associated with 112 disease phenotypes, 62 treatments, and 24 genotypes, encompassing 29,198 and 23 sample types. ExomiRHub also integrates 16,012 miRNA transcriptomes of 156 cancer subtypes from The Cancer Genome Atlas. All the data in ExomiRHub were further standardized and curated with annotations. The platform offers 25 analytical functions, including differential expression, co-expression, Weighted Gene Co-Expression Network Analysis (WGCNA), feature selection, and functional enrichment, enabling users to select samples, define groups, and customize parameters for analyses. Moreover, ExomiRHub provides a web service that allows biologists to analyze their uploaded miRNA expression data. Four additional tools were developed to evaluate the functions and targets of miRNAs and miRNA variations. Through ExomiRHub, we identified extracellular miRNA biomarkers associated with angiogenesis for monitoring glioma progression, demonstrating its potential to significantly accelerate the discovery of extracellular miRNA biomarkers.

Details

Language :
English
ISSN :
20010370
Volume :
23
Issue :
3104-3116
Database :
Directory of Open Access Journals
Journal :
Computational and Structural Biotechnology Journal
Publication Type :
Academic Journal
Accession number :
edsdoj.30e82a00de4c441f8db64428b749dd2d
Document Type :
article
Full Text :
https://doi.org/10.1016/j.csbj.2024.07.024