Genome-Wide RNA Secondary Structure Prediction
- PMID: 36705897
- DOI: 10.1007/978-1-0716-2768-6_3
Genome-Wide RNA Secondary Structure Prediction
Abstract
The information of RNA secondary structure has been widely applied to the inference of RNA function. However, a classical prediction method is not feasible to long RNAs such as mRNA due to the problems of computational time and numerical errors. To overcome those problems, sliding window methods have been applied while their results are not directly comparable to global RNA structure prediction. In this chapter, we introduce ParasoR, a method designed for parallel computation of genome-wide RNA secondary structures. To enable genome-wide prediction, ParasoR distributes dynamic programming (DP) matrices required for structure prediction to multiple computational nodes. Using the database of not the original DP variable but the ratio of variables, ParasoR can locally compute the structure scores such as stem probability or accessibility on demand. A comprehensive analysis of local secondary structures by ParasoR is expected to be a promising way to detect the statistical constraints on long RNAs.
Keywords: Genome-wide; Local structure; Maximal span constraint; Parallel computation; RNA secondary structure.
© 2023. Springer Science+Business Media, LLC, part of Springer Nature.
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