Pairing a high-resolution statistical potential with a nucleobase-centric sampling algorithm for improving RNA model refinement

Predicting RNA structure from sequence is challenging due to the relative sparsity of experimentally-determined RNA 3D structures for model training. Here, the authors propose a way to incorporate knowledge on interactions at the atomic and base–base level to refine the prediction of RNA structures....

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Autores principales:	Peng Xiong, Ruibo Wu, Jian Zhan, Yaoqi Zhou
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/3728b2ded75444fcbbd371504429c7bc
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id	oai:doaj.org-article:3728b2ded75444fcbbd371504429c7bc
record_format	dspace
spelling	oai:doaj.org-article:3728b2ded75444fcbbd371504429c7bc2021-12-02T15:43:16ZPairing a high-resolution statistical potential with a nucleobase-centric sampling algorithm for improving RNA model refinement10.1038/s41467-021-23100-42041-1723https://doaj.org/article/3728b2ded75444fcbbd371504429c7bc2021-05-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-23100-4https://doaj.org/toc/2041-1723Predicting RNA structure from sequence is challenging due to the relative sparsity of experimentally-determined RNA 3D structures for model training. Here, the authors propose a way to incorporate knowledge on interactions at the atomic and base–base level to refine the prediction of RNA structures.Peng XiongRuibo WuJian ZhanYaoqi ZhouNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Peng Xiong Ruibo Wu Jian Zhan Yaoqi Zhou Pairing a high-resolution statistical potential with a nucleobase-centric sampling algorithm for improving RNA model refinement
description	Predicting RNA structure from sequence is challenging due to the relative sparsity of experimentally-determined RNA 3D structures for model training. Here, the authors propose a way to incorporate knowledge on interactions at the atomic and base–base level to refine the prediction of RNA structures.
format	article
author	Peng Xiong Ruibo Wu Jian Zhan Yaoqi Zhou
author_facet	Peng Xiong Ruibo Wu Jian Zhan Yaoqi Zhou
author_sort	Peng Xiong
title	Pairing a high-resolution statistical potential with a nucleobase-centric sampling algorithm for improving RNA model refinement
title_short	Pairing a high-resolution statistical potential with a nucleobase-centric sampling algorithm for improving RNA model refinement
title_full	Pairing a high-resolution statistical potential with a nucleobase-centric sampling algorithm for improving RNA model refinement
title_fullStr	Pairing a high-resolution statistical potential with a nucleobase-centric sampling algorithm for improving RNA model refinement
title_full_unstemmed	Pairing a high-resolution statistical potential with a nucleobase-centric sampling algorithm for improving RNA model refinement
title_sort	pairing a high-resolution statistical potential with a nucleobase-centric sampling algorithm for improving rna model refinement
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/3728b2ded75444fcbbd371504429c7bc
work_keys_str_mv	AT pengxiong pairingahighresolutionstatisticalpotentialwithanucleobasecentricsamplingalgorithmforimprovingrnamodelrefinement AT ruibowu pairingahighresolutionstatisticalpotentialwithanucleobasecentricsamplingalgorithmforimprovingrnamodelrefinement AT jianzhan pairingahighresolutionstatisticalpotentialwithanucleobasecentricsamplingalgorithmforimprovingrnamodelrefinement AT yaoqizhou pairingahighresolutionstatisticalpotentialwithanucleobasecentricsamplingalgorithmforimprovingrnamodelrefinement
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Pairing a high-resolution statistical potential with a nucleobase-centric sampling algorithm for improving RNA model refinement

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