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

IF 2.5 Q3 BIOCHEMICAL RESEARCH METHODS
Biology Methods and Protocols Pub Date : 2024-07-02 eCollection Date: 2024-01-01 DOI:10.1093/biomethods/bpae047
Sumit Tarafder, Rahmatullah Roche, Debswapna Bhattacharya
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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.

利用变压器网络进行 RNA 3D 结构建模的前景。
变压器是神经网络的一个强大子类,它催化了越来越多的 RNA 结构建模计算方法的发展。在此,我们对基于变压器的新兴 RNA 结构预测方法的预测建模准确性进行了客观的实证研究。我们的研究揭示了这些方法之间多方面的互补性,并强调了影响预测准确性的一些关键方面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Biology Methods and Protocols
Biology Methods and Protocols Agricultural and Biological Sciences-Agricultural and Biological Sciences (all)
CiteScore
3.80
自引率
2.80%
发文量
28
审稿时长
19 weeks
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