A method for estimating energy parameters of RNAs by differentiating base-pairing probabilities.

ABSTRACT: The structure of RNA is deeply related to its function, and information about RNA substructure energy parameters is useful for predicting its structure from its sequence. RNA in cells is often modified, and these various types of modifications affect its structure and function. In recent years, the use of pseudouridine modifications in RNA vaccines has increased the importance of predicting structures that include modified bases. However, energy parameters of substructures involving modified bases have not yet been sufficiently determined. Therefore, in this paper, we propose a method for inversely calculating energy parameters from base-pairing probabilities. This method optimizes energy parameters using the same mechanism as gradient descent in deep learning. We also propose efficient co

SUBMITTER: Yamamura K 

PROVIDER: S-EPMC12684387 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature