REDfold: accurate RNA secondary structure prediction using residual encoder-decoder network.

ABSTRACT:

Background

As the RNA secondary structure is highly related to its stability and functions, the structure prediction is of great value to biological research. The traditional computational prediction for RNA secondary prediction is mainly based on the thermodynamic model with dynamic programming to find the optimal structure. However, the prediction performance based on the traditional approach is unsatisfactory for further research. Besides, the computational complexity of the structure prediction using dynamic programming is [Formula: see text]; it becomes [Formula: see text] for RNA structure with pseudoknots, which is computationally impractical for large-scale analysis.

Results

In this paper, we propose REDfold, a novel deep learning-based method for RNA secondary predi

SUBMITTER: Chen CC 

PROVIDER: S-EPMC10044938 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature