Computational Prediction of Functional MicroRNA-mRNA Interactions
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Date
2019
Journal Title
Journal ISSN
Volume Title
Publisher
Humana Press Inc
Open Access Color
Green Open Access
No
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
Abstract
Proteins have a strong influence on the phenotype and their aberrant expression leads to diseases. MicroRNAs (miRNAs) are short RNA sequences which posttranscriptionally regulate protein expression. This regulation is driven by miRNAs acting as recognition sequences for their target mRNAs within a larger regulatory machinery. A miRNA can have many target mRNAs and an mRNA can be targeted by many miRNAs which makes it difficult to experimentally discover all miRNA-mRNA interactions. Therefore, computational methods have been developed for miRNA detection and miRNA target prediction. An abundance of available computational tools makes selection difficult. Additionally, interactions are not currently the focus of investigation although they more accurately define the regulation than pre-miRNA detection or target prediction could perform alone. We define an interaction including the miRNA source and the mRNA target. We present computational methods allowing the investigation of these interactions as well as how they can be used to extend regulatory pathways. Finally, we present a list of points that should be taken into account when investigating miRNA-mRNA interactions. In the future, this may lead to better understanding of functional interactions which may pave the way for disease marker discovery and design of miRNA-based drugs.
Description
Allmer, Jens/0000-0002-2164-7335; Sacar Demirci, Muserref Duygu/0000-0003-2012-0598;
Keywords
MicroRNA, Target, Regulation, Posttranscriptional Regulation, Pathway Extension, miRNA-mRNA Interaction, Target, Sequence Analysis, RNA, Gene Expression Profiling, Computational Biology, High-Throughput Nucleotide Sequencing, MicroRNA, Pathway extension, MiRNA–mRNA interaction, Machine Learning, MicroRNAs, Databases, Genetic, Animals, Humans, Gene Regulatory Networks, RNA, Messenger, Posttranscriptional regulation, Software, Regulation
Fields of Science
0301 basic medicine, 0303 health sciences, 03 medical and health sciences
Citation
WoS Q
N/A
Scopus Q
Q4

OpenCitations Citation Count
23
Source
Methods in Molecular Biology
Volume
1912
Issue
Start Page
175
End Page
196
PlumX Metrics
Citations
Scopus : 26
PubMed : 15
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Mendeley Readers : 26
SCOPUS™ Citations
26
checked on Mar 06, 2026
Web of Science™ Citations
19
checked on Mar 06, 2026
Page Views
6
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