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

Volume / Issue Vol. 17, Issue 1
Published March 05, 2026
ISSN 2041-1723
Publisher Nature Portfolio

Journal Info

Nature Communications

Nature Portfolio

ISSN: 2041-1723 Open Access Life Sciences

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