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A Practical Guide to Phylogenetics for Nonexperts
Published on: February 5, 2014
A Practical Guide to miRNA Target Prediction
Most Mauluda Akhtar1, Luigina Micolucci2,3, Md Soriful Islam4
1Bioinformatics, Asian University for Women, Chattogram, Bangladesh. mauluda82@gmail.com.
Abstract:
MicroRNAs (miRNAs) are small endogenous noncoding RNA molecules that posttranscriptionally regulate gene expression. Since their discovery, a huge number of miRNAs have been identified in a wide range of species. Through binding to the 3' UTR of mRNA, miRNA can block translation or stimulate degradation of the targeted mRNA, thus affecting nearly all biological processes. Prediction and identification of miRNA target genes is crucial toward understanding the biology of miRNAs. Currently, a number of sophisticated bioinformatics approaches are available to perform effective prediction of miRNA target sites. In this chapter, we present the major features that most algorithms take into account to efficiently predict miRNA target: seed match, free energy, conservation, target site accessibility, and contribution of multiple binding sites. We also give an overview of the frequently used bioinformatics tools for miRNA target prediction. Understanding the basis of these prediction methodologies may help users to better select the appropriate tools and analyze their output.
Insights
MicroRNAs (miRNAs) regulate gene expression by targeting mRNA. This study details bioinformatics approaches for predicting miRNA target genes, crucial for understanding miRNA biology.
Area of Science:
- Molecular Biology
- Bioinformatics
- Genetics
Background:
- MicroRNAs (miRNAs) are small noncoding RNAs regulating gene expression post-transcriptionally.
- miRNAs impact nearly all biological processes by binding to mRNA 3' UTRs, affecting translation or degradation.
- Accurate identification of miRNA target genes is essential for elucidating miRNA functions.
Purpose of the Study:
- To present key features used in miRNA target prediction algorithms.
- To provide an overview of commonly used bioinformatics tools for miRNA target prediction.
- To guide users in selecting and analyzing miRNA target prediction tools.
Main Methods:
- Review of major algorithms for miRNA target prediction.
- Analysis of features including seed match, free energy, and conservation.
- Discussion of target site accessibility and multiple binding site contributions.
Main Results:
- Identified key features for effective miRNA target prediction.
- Outlined prevalent bioinformatics tools and methodologies.
- Highlighted the importance of understanding prediction algorithms for accurate analysis.
Conclusions:
- Bioinformatics approaches significantly aid in predicting miRNA target genes.
- Understanding prediction features and tools enhances miRNA research.
- This work provides a foundation for selecting and utilizing miRNA target prediction tools effectively.
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