DMSS: An Attention-Based Deep Learning Model for High-Quality Mass Spectrometry Prediction-Reference-Cited by-同舟云学术

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DMSS: An Attention-Based Deep Learning Model for High-Quality Mass Spectrometry Prediction

Published:2024-09 Issue:3 Volume:7 Page:577-589
ISSN:2096-0654
Container-title:Big Data Mining and Analytics
language:
Short-container-title:Big Data Min. Anal.

Author:

Ren Yihui¹,Wang Yu²,Han Wenkai³,Huang Yikang⁴,Hou Xiaoyang¹,Zhang Chunming⁵,Bu Dongbo¹,Gao Xin³,Sun Shiwei¹

Affiliation:

1. Institute of Computing Technology, Chinese Academy of Sciences,Key Lab of Intelligent Information Processing,Beijing,China,100190

2. Syneron Technology,Guangzhou,China,510000

3. King Abdullah University of Science and Technology (KAUST),Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering Division,Thuwal,Kingdom of Saudi Arabia,23955–6900

4. College of Information and Electrical Engineering, China Agricultural University,Beijing,China,100083

5. Insitute of Computing Technology, Chinese Academy of Sciences,Beijing,China,100190

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

Tsinghua University Press

Link

http://xplorestaging.ieee.org/ielx8/8254253/10654612/10654668.pdf?arnumber=10654668

Reference39 articles.

1. MASS SPECTROMETRY OF PEPTIDES AND PROTEINS

2. Mass spectrometry-based proteomics

3. Deep learning boosts sensitivity of mass spectrometry-based immunopeptidomics

4. Mitigating the missing-fragmentation problem in de novo peptide sequencing with a two-stage graph-based deep learning model

5. Prediction of peptide mass spectral libraries with machine learning

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