Why the study?
Predicting RNA secondary structure is crucial for determining RNA sequence functionality, pharmaceutical development, and tertiary structure prediction, leading researchers to develop algorithms to make accurate predictions.
Artificial intelligence methods show promise in improving the accuracy of RNA secondary structure prediction.
Undoubtedly, RNA has vital functions on organisms. As a single stranded nucleic acid, it tends to bend and twirl and it forms a stable structure of itself. This is what comes to be known as the RNA secondary structure. RNA secondary structure is of use in determining the functionalities of RNA sequences as well as in pharmaceutical developments. Furthermore, predicting the secondary structure of an RNA is a crucial step in predicting its tertiary structure, which is its three dimensional form. For the problem of RNA secondary structure, researchers have developed many algorithms over the years in an attempt to make accurate predictions. In this paper, we review some of the recent works that made use of artificial intelligence in RNA secondary structure prediction. The reviewed articles show that by the power of novel artificial intelligence methods and ensembles of the old techniques, there are promising outcomes for future research.
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Oluoch et al. (2018) studied this question.
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