Tools for Sequence-Based miRNA Target Prediction: What to Choose?
By Angela L. Riffo-Campos, I. Riquelme, Priscilla Brebi-Mieville. International Journal of Molecular Sciences, 2016
390 citations recorded by the source corpus.
MicroRNAs (miRNAs) are defined as small non-coding RNAs ~22 nt in length. They regulate gene expression at a post-transcriptional level through complementary base pairing with the target mRNA, leading to mRNA degradation and therefore blocking translation. In the last decade, the dysfunction of miRNAs has been related to the development and progression of many diseases. Currently, researchers need a method to identify precisely the miRNA targets, prior to applying experimental approaches that allow a better functional characterization of miRNAs in biological processes and can thus predict their effects. Computational prediction tools provide a rapid method to identify putative miRNA targets. However, since a large number of tools for the prediction of miRNA:mRNA interactions have been developed, all with different algorithms, the biological researcher sometimes does not know which is the best choice for his study and many times does not understand the bioinformatic basis of these tools. This review describes the biological fundamentals of these prediction tools, characterizes the main sequence-based algorithms, and offers some insights into their uses by biologists.
Subfields: Cancer Research, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/35d57140ba819134565fb78da59485f5245a8413
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Citations in the corpus
- The Potential for microRNA Therapeutics and Clinical Research (2019, background): “…used to indicate presence of a pathology and even the stage, progression, or genetic link of pathogenesis (Kocerha et al., 2011; Wang et al., 2011, 2015; Weir et al., 2011; Elfimova et al., 2012; Li et al., 2013; Recchioni et al., 2013; Scott et al., 2015; Biswas, 2018; Hu et al., 2018).”
- MIENTURNET: an interactive web tool for microRNA-target enrichment and network-based analysis (2019, methodology): “In the last few decades, many miRNA-related bioinformatic tools have been established in order to predict candidate mRNAs based on the information from sequence, structure associated free energy and evolutionary conservation [8, 9].”