Algebraic graph-assisted bidirectional transformers for molecular property prediction

Despite considerable efforts, quantitative prediction of various molecular properties remains a challenge. Here, the authors propose an algebraic graph-assisted bidirectional transformer, which can incorporate massive unlabeled molecular data into molecular representations via a self-supervised lear...

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Autores principales:	Dong Chen, Kaifu Gao, Duc Duy Nguyen, Xin Chen, Yi Jiang, Guo-Wei Wei, Feng Pan
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/964aeff00e454f149f1ac6578c7f6305
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spelling	oai:doaj.org-article:964aeff00e454f149f1ac6578c7f63052021-12-02T14:59:27ZAlgebraic graph-assisted bidirectional transformers for molecular property prediction10.1038/s41467-021-23720-w2041-1723https://doaj.org/article/964aeff00e454f149f1ac6578c7f63052021-06-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-23720-whttps://doaj.org/toc/2041-1723Despite considerable efforts, quantitative prediction of various molecular properties remains a challenge. Here, the authors propose an algebraic graph-assisted bidirectional transformer, which can incorporate massive unlabeled molecular data into molecular representations via a self-supervised learning strategy and assisted with 3D stereochemical information from graphs.Dong ChenKaifu GaoDuc Duy NguyenXin ChenYi JiangGuo-Wei WeiFeng PanNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Dong Chen Kaifu Gao Duc Duy Nguyen Xin Chen Yi Jiang Guo-Wei Wei Feng Pan Algebraic graph-assisted bidirectional transformers for molecular property prediction
description	Despite considerable efforts, quantitative prediction of various molecular properties remains a challenge. Here, the authors propose an algebraic graph-assisted bidirectional transformer, which can incorporate massive unlabeled molecular data into molecular representations via a self-supervised learning strategy and assisted with 3D stereochemical information from graphs.
format	article
author	Dong Chen Kaifu Gao Duc Duy Nguyen Xin Chen Yi Jiang Guo-Wei Wei Feng Pan
author_facet	Dong Chen Kaifu Gao Duc Duy Nguyen Xin Chen Yi Jiang Guo-Wei Wei Feng Pan
author_sort	Dong Chen
title	Algebraic graph-assisted bidirectional transformers for molecular property prediction
title_short	Algebraic graph-assisted bidirectional transformers for molecular property prediction
title_full	Algebraic graph-assisted bidirectional transformers for molecular property prediction
title_fullStr	Algebraic graph-assisted bidirectional transformers for molecular property prediction
title_full_unstemmed	Algebraic graph-assisted bidirectional transformers for molecular property prediction
title_sort	algebraic graph-assisted bidirectional transformers for molecular property prediction
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/964aeff00e454f149f1ac6578c7f6305
work_keys_str_mv	AT dongchen algebraicgraphassistedbidirectionaltransformersformolecularpropertyprediction AT kaifugao algebraicgraphassistedbidirectionaltransformersformolecularpropertyprediction AT ducduynguyen algebraicgraphassistedbidirectionaltransformersformolecularpropertyprediction AT xinchen algebraicgraphassistedbidirectionaltransformersformolecularpropertyprediction AT yijiang algebraicgraphassistedbidirectionaltransformersformolecularpropertyprediction AT guoweiwei algebraicgraphassistedbidirectionaltransformersformolecularpropertyprediction AT fengpan algebraicgraphassistedbidirectionaltransformersformolecularpropertyprediction
_version_	1718389216894779392

Algebraic graph-assisted bidirectional transformers for molecular property prediction

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