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a catalog of worldwide biological databases

Database Profile

miRPathDB

General information

URL: https://mpd.bioinf.uni-sb.de/
Full name: miRNA Pathway Dictionary Database
Description: miRPathDB, with which we aim to augment available target pathway web-servers by providing researches easy access to the information which pathways are regulated by a miRNA, which miRNAs target a pathway and how specific the regulations are.
Year founded: 2017
Last update: 2017-01-01
Version: v 1.0
Accessibility:
Accessible
Country/Region: Germany

Classification & Tag

Data type:
RNA
Data object:
Database category:
Major species:
Keywords:

Contact information

University/Institution: Saarland University
Address: Chair for Clinical Bioinformatics, Saarland Informatics Campus
City: Saarbruecken
Province/State: Saarland
Country/Region: Germany
Contact name (PI/Team): Andreas Keller
Contact email (PI/Helpdesk): andreas.keller@ccb.uni-saarland.de

Publications

31691816
miRPathDB 2.0: a novel release of the miRNA Pathway Dictionary Database. [PMID: 31691816]
Kehl T, Kern F, Backes C, Fehlmann T, Stöckel D, Meese E, Lenhof HP, Keller A.

Since the initial release of miRPathDB, tremendous progress has been made in the field of microRNA (miRNA) research. New miRNA reference databases have emerged, a vast amount of new miRNA candidates has been discovered and the number of experimentally validated target genes has increased considerably. Hence, the demand for a major upgrade of miRPathDB, including extended analysis functionality and intuitive visualizations of query results has emerged. Here, we present the novel release 2.0 of the miRNA Pathway Dictionary Database (miRPathDB) that is freely accessible at https://mpd.bioinf.uni-sb.de/. miRPathDB 2.0 comes with a ten-fold increase of pre-processed data. In total, the updated database provides putative associations between 27 452 (candidate) miRNAs, 28 352 targets and 16 833 pathways for Homo sapiens, as well as interactions of 1978 miRNAs, 24 898 targets and 6511 functional categories for Mus musculus. Additionally, we analyzed publications citing miRPathDB to identify common use-cases and further extensions. Based on this evaluation, we added new functionality for interactive visualizations and down-stream analyses of bulk queries. In summary, the updated version of miRPathDB, with its new custom-tailored features, is one of the most comprehensive and advanced resources for miRNAs and their target pathways.

Nucleic Acids Res. 2020:48(D1) | 165 Citations (from Europe PMC, 2025-12-13)
27742822
miRPathDB: a new dictionary on microRNAs and target pathways. [PMID: 27742822]
Backes C, Kehl T, Stöckel D, Fehlmann T, Schneider L, Meese E, Lenhof HP, Keller A.

In the last decade, miRNAs and their regulatory mechanisms have been intensively studied and many tools for the analysis of miRNAs and their targets have been developed. We previously presented a dictionary on single miRNAs and their putative target pathways. Since then, the number of miRNAs has tripled and the knowledge on miRNAs and targets has grown substantially. This, along with changes in pathway resources such as KEGG, leads to an improved understanding of miRNAs, their target genes and related pathways. Here, we introduce the miRNA Pathway Dictionary Database (miRPathDB), freely accessible at https://mpd.bioinf.uni-sb.de/ With the database we aim to complement available target pathway web-servers by providing researchers easy access to the information which pathways are regulated by a miRNA, which miRNAs target a pathway and how specific these regulations are. The database contains a large number of miRNAs (2595 human miRNAs), different miRNA target sets (14 773 experimentally validated target genes as well as 19 281 predicted targets genes) and a broad selection of functional biochemical categories (KEGG-, WikiPathways-, BioCarta-, SMPDB-, PID-, Reactome pathways, functional categories from gene ontology (GO), protein families from Pfam and chromosomal locations totaling 12 875 categories). In addition to Homo sapiens, also Mus musculus data are stored and can be compared to human target pathways. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Nucleic Acids Res. 2017:45(D1) | 90 Citations (from Europe PMC, 2025-12-13)
29291020
About miRNAs, miRNA seeds, target genes and target pathways. [PMID: 29291020]
Kehl T, Backes C, Kern F, Fehlmann T, Ludwig N, Meese E, Lenhof HP, Keller A.

miRNAs are typically repressing gene expression by binding to the 3' UTR, leading to degradation of the mRNA. This process is dominated by the eight-base seed region of the miRNA. Further, miRNAs are known not only to target genes but also to target significant parts of pathways. A logical line of thoughts is: miRNAs with similar (seed) sequence target similar sets of genes and thus similar sets of pathways. By calculating similarity scores for all 3.25 million pairs of 2,550 human miRNAs, we found that this pattern frequently holds, while we also observed exceptions. Respective results were obtained for both, predicted target genes as well as experimentally validated targets. We note that miRNAs target gene set similarity follows a bimodal distribution, pointing at a set of 282 miRNAs that seems to target genes with very high specificity. Further, we discuss miRNAs with different (seed) sequences that nonetheless regulate similar gene sets or pathways. Most intriguingly, we found miRNA pairs that regulate different gene sets but similar pathways such as miR-6886-5p and miR-3529-5p. These are jointly targeting different parts of the MAPK signaling cascade. The main goal of this study is to provide a general overview on the results, to highlight a selection of relevant results on miRNAs, miRNA seeds, target genes and target pathways and to raise awareness for artifacts in respective comparisons. The full set of information that allows to infer detailed results on each miRNA has been included in miRPathDB, the miRNA target pathway database (https://mpd.bioinf.uni-sb.de).

Oncotarget. 2017:8(63) | 106 Citations (from Europe PMC, 2025-12-13)

Ranking

All databases:
375/6895 (94.576%)
Pathway:
28/451 (94.013%)
375
Total Rank
344
Citations
43
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Record metadata

Created on: 2017-02-13
Curated by:
Chang Liu [2020-11-07]
Yang Zhang [2018-01-27]
Shixiang Sun [2017-02-13]