DeepSP: A Deep Learning Framework for Spatial Proteomics-Reference-Cited by-同舟云学术

DeepSP: A Deep Learning Framework for Spatial Proteomics

Published:2023-06-14 Issue:7 Volume:22 Page:2186-2198
ISSN:1535-3893
Container-title:Journal of Proteome Research
language:en
Short-container-title:J. Proteome Res.

Author:

Wang Bing¹²^ORCID,Zhang Xiangzheng¹,Xu Chen¹,Han Xudong¹²,Wang Yue¹,Situ Chenghao¹,Li Yan³,Guo Xuejiang¹^ORCID

Affiliation:

1. Department of Histology and Embryology, State Key Laboratory of Reproductive Medicine and Offspring Health, Nanjing Medical University, Nanjing 211166, China

2. School of Medicine, Southeast University, Nanjing 210009, China

3. Department of Clinical Laboratory, Sir Run Run Hospital, Nanjing Medical University, Nanjing 211100, China

Funder

National Key Research and Development Program of China

Jiangsu Provincial Commission of Health and Family Planning

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Subject

General Chemistry,Biochemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jproteome.2c00394

Reference56 articles.

1. MULocDeep: A deep-learning framework for protein subcellular and suborganellar localization prediction with residue-level interpretation

2. Assessing sub-cellular resolution in spatial proteomics experiments

3. Protein localization in disease and therapy

4. Protein localization as a principal feature of the etiology and comorbidity of genetic diseases

5. Localization of Organelle Proteins by Isotope Tagging: Current status and potential applications in drug discovery research

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