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The landscape of RNA 3D structure modeling with transformer networks

Sumit Tarafder¹, Rahmatullah Roche¹, Debswapna Bhattacharya¹

¹Department of Computer Science, Virginia Tech, Blacksburg, VA 24061, United States.

Biology Methods & Protocols

|July 15, 2024

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.

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