The landscape of RNA 3D structure modeling with transformer networks.

ABSTRACT: Transformers are a powerful subclass of neural networks catalyzing the development of a growing number of computational methods for RNA structure modeling. Here, we conduct an objective and empirical study of the predictive modeling accuracy of the emerging transformer-based methods for RNA structure prediction. Our study reveals multi-faceted complementarity between the methods and underscores some key aspects that affect the prediction accuracy.

SUBMITTER: Tarafder S 

PROVIDER: S-EPMC11244692 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature