Proteins have a strong influence on the phenotype and their aberrant expression leads to diseases. MicroRNAs (miRNAs) are short RNA sequences which posttranscriptionally regulate protein expression. This regulation is driven by miRNAs acting as recognition sequences for their target mRNAs within a larger regulatory machinery. A miRNA can have many target mRNAs and an mRNA can be targeted by many miRNAs which makes it difficult to experimentally discover all miRNA–mRNA interactions. Therefore, computational methods have been developed for miRNA detection and miRNA target prediction. An abundance of available computational tools makes selection difficult. Additionally, interactions are not currently the focus of investigation although they more accurately define the regulation than pre-miRNA detection or target prediction could perform alone. We define an interaction including the miRNA source and the mRNA target. We present computational methods allowing the investigation of these interactions as well as how they can be used to extend regulatory pathways. Finally, we present a list of points that should be taken into account when investigating miRNA–mRNA interactions. In the future, this may lead to better understanding of functional interactions which may pave the way for disease marker discovery and design of miRNA-based drugs.
|Title of host publication||Computational Biology of Non-Coding RNA|
|Editors||X. Lai, S.K. Gupta, J. Vera|
|Place of Publication||New York|
|Publication status||Published - 12 Jan 2019|
|Name||Methods in Molecular Biology|
Saçar Demirci, , M. D., Yousef, M., & Allmer, J. (2019). Computational Prediction of Functional MicroRNA–mRNA Interactions. In X. Lai, S. K. Gupta, & J. Vera (Eds.), Computational Biology of Non-Coding RNA (pp. 175-196). (Methods in Molecular Biology; Vol. 1912). New York: Springer. https://doi.org/10.1007/978-1-4939-8982-9_7