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Updated: Mar 7, 2026
Detection of miRNA Targets in High-throughput Using the 3'LIFE Assay
Published on: May 25, 2015
miRNAs target databases: developmental methods and target identification techniques with functional annotations
1Department of Biological Science and Engineering, Maulana Azad National Institute of Technology, Bhopal, 462003, India. nagendravns@gmail.com.
Purpose:
microRNA (miRNA) regulates diverse biological mechanisms and metabolisms in plants and animals. Thus, the discoveries of miRNA has revolutionized the life sciences and medical research.The miRNA represses and cleaves the targeted mRNA by binding perfect or near perfect or imperfect complementary base pairs by RNA-induced silencing complex (RISC) formation during biogenesis process. One miRNA interacts with one or more mRNA genes and vice versa, hence takes part in causing various diseases. In this paper, the different microRNA target databases and their functional annotations developed by various researchers have been reviewed. The concurrent research review aims at comprehending the significance of miRNA and presenting the existing status of annotated miRNA target resources built by researchers henceforth discovering the knowledge for diagnosis and prognosis.
Methods And Results:
This review discusses the applications and developmental methodologies for constructing target database as well as the utility of user interface design. An integrated architecture is drawn and a graphically comparative study of present status of miRNA targets in diverse diseases and various biological processes is performed. These databases comprise of information such as miRNA target-associated disease, transcription factor binding sites (TFBSs) in miRNA genomic locations, polymorphism in miRNA target, A-to-I edited target, Gene Ontology (GO), genome annotations, KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, target expression analysis, TF-miRNA and miRNA-mRNA interaction networks, drugs-targets interactions, etc.
Conclusion:
miRNA target databases contain diverse experimentally and computationally predicted target through various algorithms. The comparison of various miRNA target database has been performed on various parameters. The computationally predicted target databases suffer from false positive information as there is no common theory for prediction of miRNA targets. The review conclusion emphasizes the need of more intelligent computational improvement for the miRNA target identification, their functional annotations and datasbase development.
Insights
MicroRNA (miRNA) databases are crucial for understanding gene regulation and disease. This review highlights current miRNA target databases, their annotations, and the need for improved computational methods for accurate target identification and functional analysis.
Area of Science:
- Life sciences and medical research
- Plant and animal biology
- Gene regulation and expression
Background:
- MicroRNAs (miRNAs) are key regulators of biological processes and metabolism.
- miRNA biogenesis involves RNA-induced silencing complex (RISC) formation, leading to mRNA repression or cleavage.
- Dysregulation of miRNA activity is implicated in various diseases.
Purpose of the Study:
- To review existing microRNA target databases and their functional annotations.
- To comprehend the significance of miRNA in biological systems and disease.
- To present the current status of annotated miRNA target resources for diagnosis and prognosis.
Main Methods:
- Review of diverse miRNA target databases and their applications.
- Discussion of database construction methodologies and user interface design.
- Comparative study of miRNA targets in diseases and biological processes, including associated data types like TFBSs, polymorphism, GO, KEGG pathways, and interaction networks.
Main Results:
- miRNA target databases integrate various data, including disease associations, genomic information, and pathway analysis.
- Databases contain both experimentally validated and computationally predicted miRNA targets.
- Computational prediction methods often yield false positives due to a lack of standardized prediction theories.
Conclusions:
- Existing miRNA target databases offer valuable resources for research.
- There is a critical need for enhanced computational approaches for accurate miRNA target identification.
- Further development of intelligent algorithms and robust database frameworks is essential for advancing miRNA research and its clinical applications.
