A unified drug–target interaction prediction framework based on knowledge graph and recommendation system

Prediction of drug-target interactions (DTI) plays a vital role in drug development through applications in various areas, such as virtual screening for lead discovery, drug repurposing and identification of potential drug side effects. Here, the authors develop a unified framework for DTI predictio...

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Autores principales:	Qing Ye, Chang-Yu Hsieh, Ziyi Yang, Yu Kang, Jiming Chen, Dongsheng Cao, Shibo He, Tingjun Hou
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/feb43093b20a4dbf8bf7f4189d80feff
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spelling	oai:doaj.org-article:feb43093b20a4dbf8bf7f4189d80feff2021-11-28T12:31:10ZA unified drug–target interaction prediction framework based on knowledge graph and recommendation system10.1038/s41467-021-27137-32041-1723https://doaj.org/article/feb43093b20a4dbf8bf7f4189d80feff2021-11-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-27137-3https://doaj.org/toc/2041-1723Prediction of drug-target interactions (DTI) plays a vital role in drug development through applications in various areas, such as virtual screening for lead discovery, drug repurposing and identification of potential drug side effects. Here, the authors develop a unified framework for DTI prediction by combining a knowledge graph and a recommendation system.Qing YeChang-Yu HsiehZiyi YangYu KangJiming ChenDongsheng CaoShibo HeTingjun HouNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Qing Ye Chang-Yu Hsieh Ziyi Yang Yu Kang Jiming Chen Dongsheng Cao Shibo He Tingjun Hou A unified drug–target interaction prediction framework based on knowledge graph and recommendation system
description	Prediction of drug-target interactions (DTI) plays a vital role in drug development through applications in various areas, such as virtual screening for lead discovery, drug repurposing and identification of potential drug side effects. Here, the authors develop a unified framework for DTI prediction by combining a knowledge graph and a recommendation system.
format	article
author	Qing Ye Chang-Yu Hsieh Ziyi Yang Yu Kang Jiming Chen Dongsheng Cao Shibo He Tingjun Hou
author_facet	Qing Ye Chang-Yu Hsieh Ziyi Yang Yu Kang Jiming Chen Dongsheng Cao Shibo He Tingjun Hou
author_sort	Qing Ye
title	A unified drug–target interaction prediction framework based on knowledge graph and recommendation system
title_short	A unified drug–target interaction prediction framework based on knowledge graph and recommendation system
title_full	A unified drug–target interaction prediction framework based on knowledge graph and recommendation system
title_fullStr	A unified drug–target interaction prediction framework based on knowledge graph and recommendation system
title_full_unstemmed	A unified drug–target interaction prediction framework based on knowledge graph and recommendation system
title_sort	unified drug–target interaction prediction framework based on knowledge graph and recommendation system
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/feb43093b20a4dbf8bf7f4189d80feff
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A unified drug–target interaction prediction framework based on knowledge graph and recommendation system

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