核糖核酸
计算机科学
核酸结构
人工智能
机器学习
计算生物学
生物
基因
生物化学
作者
Xiujuan Ou,Yi Zhang,Yiduo Xiong,Yi Xiao
标识
DOI:10.1021/acs.jcim.2c00939
摘要
RNA molecules carry out various cellular functions, and understanding the mechanisms behind their functions requires the knowledge of their 3D structures. Different types of computational methods have been developed to model RNA 3D structures over the past decade. These methods were widely used by researchers although their performance needs to be further improved. Recently, along with these traditional methods, machine-learning techniques have been increasingly applied to RNA 3D structure prediction and show significant improvement in performance. Here we shall give a brief review of the traditional methods and recent related advances in machine-learning approaches for RNA 3D structure prediction.
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