DiNovo enables high-coverage and high-confidence de novo peptide sequencing via mirror proteases and deep learning
Z
Zixuan Cao
X
Xueli Peng
D
Di Zhang
P
Piyu Zhou
L
Li Kang
H
Hao Chi
(Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii at Manoa)
R
Ruitao Wu
(State Key Laboratory of Porous Materials for Separation and Conversion, Collaborative Innovation Center of Chemistry for Energy Material, Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, Key Laboratory of Computational Physical Science, Department of Chemistry)
Z
Zhiyuan Cheng
Y
Yao Zhang
J
Jiaxing Dai
Y
Yanchang Li
L
Lijin Yao
X
Xinming Li
Y
Yaoyu He
J
Jinghan Yang
H
Haipeng Wang
P
Ping Xu
Y
Yan Fu
Article Details
Journal
Nature Communications
Volume / Issue
Vol. 17, Issue 1
Published
March 05, 2026
ISSN
2041-1723
Publisher
Nature Portfolio
Authors (18)
Z
Zixuan Cao
X
Xueli Peng
D
Di Zhang
P
Piyu Zhou
L
Li Kang
H
Hao Chi
Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii at Manoa
R
Ruitao Wu
State Key Laboratory of Porous Materials for Separation and Conversion, Collaborative Innovation Center of Chemistry for Energy Material, Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, Key Laboratory of Computational Physical Science, Department of Chemistry
Z
Zhiyuan Cheng
Y
Yao Zhang
J
Jiaxing Dai
Y
Yanchang Li
L
Lijin Yao
X
Xinming Li
Y
Yaoyu He
J
Jinghan Yang
H
Haipeng Wang
P
Ping Xu
Y
Yan Fu
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