人工智能
核糖核酸
深度学习
透视图(图形)
机器学习
核酸结构
训练集
计算机科学
计算生物学
生物
基因
遗传学
作者
Raphael J.L. Townshend,Stephan Eismann,Andrew Watkins,Ramya Rangan,Masha Karelina,Rhiju Das,Ron O. Dror
出处
期刊:Science
[American Association for the Advancement of Science (AAAS)]
日期:2021-08-26
卷期号:373 (6558): 1047-1051
被引量:254
标识
DOI:10.1126/science.abe5650
摘要
Machine learning solves RNA puzzles RNA molecules fold into complex three-dimensional shapes that are difficult to determine experimentally or predict computationally. Understanding these structures may aid in the discovery of drugs for currently untreatable diseases. Townshend et al . introduced a machine-learning method that significantly improves prediction of RNA structures (see the Perspective by Weeks). Most other recent advances in deep learning have required a tremendous amount of data for training. The fact that this method succeeds given very little training data suggests that related methods could address unsolved problems in many fields where data are scarce. —DJ
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