中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 计算技术研究所
  3. 中国科学院计算技术研究所
  4. 中国科学院计算技术研究所期刊论文
  5. 英文
Accurate prediction of RNA secondary structure including pseudoknots through solving minimum-cost flow with learned potentials

文献类型：期刊论文

作者Gong, Tiansu2,3; Ju, Fusong2,3; Bu, Dongbo1,2,3
刊名COMMUNICATIONS BIOLOGY
出版日期2024-03-09
卷号7期号:1页码:13
DOI10.1038/s42003-024-05952-w
英文摘要Pseudoknots are key structure motifs of RNA and pseudoknotted RNAs play important roles in a variety of biological processes. Here, we present KnotFold, an accurate approach to the prediction of RNA secondary structure including pseudoknots. The key elements of KnotFold include a learned potential function and a minimum-cost flow algorithm to find the secondary structure with the lowest potential. KnotFold learns the potential from the RNAs with known structures using an attention-based neural network, thus avoiding the inaccuracy of hand-crafted energy functions. The specially designed minimum-cost flow algorithm used by KnotFold considers all possible combinations of base pairs and selects from them the optimal combination. The algorithm breaks the restriction of nested base pairs required by the widely used dynamic programming algorithms, thus enabling the identification of pseudoknots. Using 1,009 pseudoknotted RNAs as representatives, we demonstrate the successful application of KnotFold in predicting RNA secondary structures including pseudoknots with accuracy higher than the state-of-the-art approaches. We anticipate that KnotFold, with its superior accuracy, will greatly facilitate the understanding of RNA structures and functionalities. Presenting KnotFold, an application for accurately predicting RNA secondary structures, including pseudoknots.
资助项目the National Key Research and Development Program of China (2020YFA0907000), and the National Natural Science Foundation of China (32370657, 32271297, 82130055, 62072435)[2020YFA0907000] ; National Key Research and Development Program of China[32370657] ; National Key Research and Development Program of China[32271297] ; National Key Research and Development Program of China[82130055] ; National Key Research and Development Program of China[62072435] ; National Natural Science Foundation of China ; ICT Computer-X center, Chinese Academy of Sciences
WOS研究方向Life Sciences & Biomedicine - Other Topics ; Science & Technology - Other Topics
语种英语
WOS记录号WOS:001185102800004
出版者NATURE PORTFOLIO
源URL[http://119.78.100.204/handle/2XEOYT63/38798]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Bu, Dongbo
作者单位1.Henan Acad Sci, Cent China Artificial Intelligence Res Inst, Zhengzhou 450046, Henan, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100190, Peoples R China
3.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Inst Comp Technol, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Gong, Tiansu,Ju, Fusong,Bu, Dongbo. Accurate prediction of RNA secondary structure including pseudoknots through solving minimum-cost flow with learned potentials[J]. COMMUNICATIONS BIOLOGY,2024,7(1):13.
APA Gong, Tiansu,Ju, Fusong,&Bu, Dongbo.(2024).Accurate prediction of RNA secondary structure including pseudoknots through solving minimum-cost flow with learned potentials.COMMUNICATIONS BIOLOGY,7(1),13.
MLA Gong, Tiansu,et al."Accurate prediction of RNA secondary structure including pseudoknots through solving minimum-cost flow with learned potentials".COMMUNICATIONS BIOLOGY 7.1(2024):13.

入库方式： OAI收割

来源：计算技术研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。