Nature Communications

ESM-Ezy: a deep learning strategy for the mining of novel multicopper oxidases with superior properties

H Hui Qian Y Yuxuan Wang X Xibin Zhou T Tao Gu H Hui Wang H Hao Lyu (Department of Chemical Engineering) Z Zhikai Li (State Key Laboratory for Porous Metal Materials, Shaanxi Key Laboratory of New Conceptual Sensors and Molecular Materials, Shaanxi International Research Center for Soft Matter, Xi’an Key Laboratory of Sustainable Polymer Materials, School of Materials Science and Engineering) X Xiuxu Li H Huan Zhou C Chengchen Guo F Fajie Yuan (School of Engineering, Westlake University, 600 Dunyu Road, Hangzhou 310030, China) Y Yajie Wang (School of Engineering, Westlake University, Hangzhou, China.)
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Article Details

Volume / Issue Vol. 16, Issue 1
Published April 06, 2025
ISSN 2041-1723
Publisher Nature Portfolio

Journal Info

Nature Communications

Nature Portfolio
ISSN: 2041-1723 Open Access Life Sciences

Authors (12)

H

Hui Qian

Y

Yuxuan Wang

X

Xibin Zhou

T

Tao Gu

H

Hui Wang

H

Hao Lyu

Department of Chemical Engineering

Z

Zhikai Li

State Key Laboratory for Porous Metal Materials, Shaanxi Key Laboratory of New Conceptual Sensors and Molecular Materials, Shaanxi International Research Center for Soft Matter, Xi’an Key Laboratory of Sustainable Polymer Materials, School of Materials Science and Engineering

X

Xiuxu Li

H

Huan Zhou

C

Chengchen Guo

F

Fajie Yuan

School of Engineering, Westlake University, 600 Dunyu Road, Hangzhou 310030, China

Y

Yajie Wang

School of Engineering, Westlake University, Hangzhou, China.

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