Mathematical Models in Biology by Valeria Zazzu Maria Brigida Ferraro & Mario R. Guarracino

Author:Valeria Zazzu, Maria Brigida Ferraro & Mario R. Guarracino
Language: eng
Format: epub
Publisher: Springer International Publishing, Cham

4 Conclusions

In silico methods for studying miRNA biogenesis, ranging from statistical models of promoter recognition and transcription factor binding site prediction to predictive models of miRNA processing, enable a better understanding of miRNA-mediated regulation in tissue-specific networks. Recent progress in the field of NGS resulted in a plethora of high-throughput and high-quality datasets in the last few years. This enabled the development of data-driven computational approaches which make use of such data and combine them with traditional sequence signals, in order to get more accurate prediction of miRNA promoters. Although the basics of the miRNA biogenesis pathway are known, there are still many unsolved questions. For example, several regulatory factors might be involved in miRNA regulation at different levels. Although some regulators of miRNA transcription and processing have been predicted and experimentally validated, more sophisticated in silico methods are needed to discover more of these factors and predict how they affect miRNA biogenesis.

RNA binding proteins interact with both pri-miRNAs in addition to intermediate miRNA products at different stages of their regulation. High-throughput sequencing of RNA sites bound by a particular protein will reveal more aspects about miRNA regulation, as well as enable more reliable identification of targets which are physiologically relevant.

Although observations from different sources need to be unified in a coherent framework, it is clear that targeted computational approaches can help linking different evidence from several genomic datasets and give a significant contribution to discover additional details about miRNA-mediated regulation.

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