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Updated: Oct 25, 2025
Detection of miRNA Targets in High-throughput Using the 3'LIFE Assay
Published on: May 25, 2015
Recent Development of Bioinformatics Tools for microRNA Target Prediction
Mst Shamima Khatun1, Md Ashad Alam2, Watshara Shoombuatong3
1Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, Fukuoka 820-8502, Japan.
Abstract:
MicroRNAs (miRNAs) are central players that regulate the post-transcriptional processes of gene expression. Binding of miRNAs to target mRNAs can repress their translation by inducing the degradation or by inhibiting the translation of the target mRNAs. Highthroughput experimental approaches for miRNA target identification are costly and timeconsuming, depending on various factors. It is vitally important to develop bioinformatics methods for accurately predicting miRNA targets. With the increase of RNA sequences in the post-genomic era, bioinformatics methods are being developed for miRNA studies especially for miRNA target prediction. This review summarizes the current development of state-of-the-art bioinformatics tools for miRNA target prediction, points out the progress and limitations of the available miRNA databases, and their working principles. Finally, we discuss the caveat and perspectives of the next-generation algorithms for the prediction of miRNA targets.
Insights
Predicting microRNA (miRNA) targets is crucial for understanding gene regulation. This review covers bioinformatics tools and databases for miRNA target identification, discussing their progress and future directions.
Area of Science:
- Molecular Biology
- Bioinformatics
- Genomics
Background:
- MicroRNAs (miRNAs) are key regulators of post-transcriptional gene expression.
- miRNA binding to target messenger RNAs (mRNAs) can inhibit translation or induce degradation.
- Experimental miRNA target identification is expensive and time-consuming.
Purpose of the Study:
- To review state-of-the-art bioinformatics tools for miRNA target prediction.
- To assess the progress and limitations of current miRNA databases.
- To discuss future perspectives for next-generation miRNA target prediction algorithms.
Main Methods:
- Literature review of bioinformatics tools and databases for miRNA target prediction.
- Analysis of working principles, progress, and limitations of existing methods.
- Discussion of emerging trends and challenges in the field.
Main Results:
- Numerous bioinformatics tools and databases have been developed for miRNA target prediction.
- These tools vary in their underlying algorithms and performance.
- Current databases offer valuable resources but have limitations in accuracy and scope.
Conclusions:
- Bioinformatics approaches are essential for efficient miRNA target prediction.
- Further development of sophisticated algorithms and comprehensive databases is needed.
- Next-generation algorithms should address current caveats for improved accuracy and broader applicability.
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