ECNet is an evolutionary context-integrated deep learning framework for protein engineering

Protein engineering is an active area of research in which machine learning has proven quite powerful. Here, the authors present a deep learning method that integrates both general and protein-specific sequence representations to improve the engineering of one’s protein of interest.

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Autores principales:	Yunan Luo, Guangde Jiang, Tianhao Yu, Yang Liu, Lam Vo, Hantian Ding, Yufeng Su, Wesley Wei Qian, Huimin Zhao, Jian Peng
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/0bb0a79962b04f8bba4f09b68761698c
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spelling	oai:doaj.org-article:0bb0a79962b04f8bba4f09b68761698c2021-12-02T17:37:36ZECNet is an evolutionary context-integrated deep learning framework for protein engineering10.1038/s41467-021-25976-82041-1723https://doaj.org/article/0bb0a79962b04f8bba4f09b68761698c2021-09-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-25976-8https://doaj.org/toc/2041-1723Protein engineering is an active area of research in which machine learning has proven quite powerful. Here, the authors present a deep learning method that integrates both general and protein-specific sequence representations to improve the engineering of one’s protein of interest.Yunan LuoGuangde JiangTianhao YuYang LiuLam VoHantian DingYufeng SuWesley Wei QianHuimin ZhaoJian PengNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Yunan Luo Guangde Jiang Tianhao Yu Yang Liu Lam Vo Hantian Ding Yufeng Su Wesley Wei Qian Huimin Zhao Jian Peng ECNet is an evolutionary context-integrated deep learning framework for protein engineering
description	Protein engineering is an active area of research in which machine learning has proven quite powerful. Here, the authors present a deep learning method that integrates both general and protein-specific sequence representations to improve the engineering of one’s protein of interest.
format	article
author	Yunan Luo Guangde Jiang Tianhao Yu Yang Liu Lam Vo Hantian Ding Yufeng Su Wesley Wei Qian Huimin Zhao Jian Peng
author_facet	Yunan Luo Guangde Jiang Tianhao Yu Yang Liu Lam Vo Hantian Ding Yufeng Su Wesley Wei Qian Huimin Zhao Jian Peng
author_sort	Yunan Luo
title	ECNet is an evolutionary context-integrated deep learning framework for protein engineering
title_short	ECNet is an evolutionary context-integrated deep learning framework for protein engineering
title_full	ECNet is an evolutionary context-integrated deep learning framework for protein engineering
title_fullStr	ECNet is an evolutionary context-integrated deep learning framework for protein engineering
title_full_unstemmed	ECNet is an evolutionary context-integrated deep learning framework for protein engineering
title_sort	ecnet is an evolutionary context-integrated deep learning framework for protein engineering
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/0bb0a79962b04f8bba4f09b68761698c
work_keys_str_mv	AT yunanluo ecnetisanevolutionarycontextintegrateddeeplearningframeworkforproteinengineering AT guangdejiang ecnetisanevolutionarycontextintegrateddeeplearningframeworkforproteinengineering AT tianhaoyu ecnetisanevolutionarycontextintegrateddeeplearningframeworkforproteinengineering AT yangliu ecnetisanevolutionarycontextintegrateddeeplearningframeworkforproteinengineering AT lamvo ecnetisanevolutionarycontextintegrateddeeplearningframeworkforproteinengineering AT hantianding ecnetisanevolutionarycontextintegrateddeeplearningframeworkforproteinengineering AT yufengsu ecnetisanevolutionarycontextintegrateddeeplearningframeworkforproteinengineering AT wesleyweiqian ecnetisanevolutionarycontextintegrateddeeplearningframeworkforproteinengineering AT huiminzhao ecnetisanevolutionarycontextintegrateddeeplearningframeworkforproteinengineering AT jianpeng ecnetisanevolutionarycontextintegrateddeeplearningframeworkforproteinengineering
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ECNet is an evolutionary context-integrated deep learning framework for protein engineering

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