Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

DeepCSO: A Deep-Learning Network Approach to Predicting Cysteine S-Sulphenylation Sites
Xiaru Lyu, Shuhao Li, Chunyang Jiang, et al.
Frontiers in Cell and Developmental Biology (2020) Vol. 8
Open Access | Times Cited: 20

Showing 20 citing articles:

Mini-review: Recent advances in post-translational modification site prediction based on deep learning
Lingkuan Meng, Wai‐Sum Chan, Lei Huang, et al.
Computational and Structural Biotechnology Journal (2022) Vol. 20, pp. 3522-3532
Open Access | Times Cited: 31
DeepNphos: A deep-learning architecture for prediction of N-phosphorylation sites
Xulin Chang, Yafei Zhu, Yu Chen, et al.
Computers in Biology and Medicine (2024) Vol. 170, pp. 108079-108079
Closed Access | Times Cited: 4
Lactylation prediction models based on protein sequence and structural feature fusion
Yehong Yang, Juntao Yang, Jiang-Feng Liu
Briefings in Bioinformatics (2024) Vol. 25, Iss. 2
Open Access | Times Cited: 3
ResSUMO: A Deep Learning Architecture Based on Residual Structure for Prediction of Lysine SUMOylation Sites
Yafei Zhu, Yuhai Liu, Yu Chen, et al.
Cells (2022) Vol. 11, Iss. 17, pp. 2646-2646
Open Access | Times Cited: 13
CNNArginineMe: A CNN structure for training models for predicting arginine methylation sites based on the One-Hot encoding of peptide sequence
Jiaojiao Zhao, Haoqiang Jiang, Guoyang Zou, et al.
Frontiers in Genetics (2022) Vol. 13
Open Access | Times Cited: 10
CysModDB: a comprehensive platform with the integration of manually curated resources and analysis tools for cysteine posttranslational modifications
Yanzheng Meng, Lin Zhang, Laizhi Zhang, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 6
Open Access | Times Cited: 10
DeepKcrot: A Deep-Learning Architecture for General and Species-Specific Lysine Crotonylation Site Prediction
Xilin Wei, Yutong Sha, Yiming Zhao, et al.
IEEE Access (2021) Vol. 9, pp. 49504-49513
Open Access | Times Cited: 13
ECM-LSE: Prediction of Extracellular Matrix Proteins Using Deep Latent Space Encoding of k-Spaced Amino Acid Pairs
Ubaid M. Al‐Saggaf, Muhammad Usman, Imran Naseem, et al.
Frontiers in Bioengineering and Biotechnology (2021) Vol. 9
Open Access | Times Cited: 12
PlantNh-Kcr: a deep learning model for predicting non-histone crotonylation sites in plants
Yanming Jiang, Renxiang Yan, Xiaofeng Wang
Plant Methods (2024) Vol. 20, Iss. 1
Open Access | Times Cited: 1
DeepSADPr: A hybrid-learning architecture for serine ADP-ribosylation site prediction
Yutong Sha, Chenglong Ma, Xilin Wei, et al.
Methods (2021) Vol. 203, pp. 575-583
Closed Access | Times Cited: 11
A systematic review on the state-of-the-art strategies for protein representation
Zixuan Yue, Tianci Yan, Hongquan Xu, et al.
Computers in Biology and Medicine (2022) Vol. 152, pp. 106440-106440
Closed Access | Times Cited: 6
Using ATCLSTM-Kcr to predict and generate the human lysine crotonylation database
Yehong Yang, Songfeng Wu, Jie Kong, et al.
Journal of Proteomics (2023) Vol. 281, pp. 104905-104905
Closed Access | Times Cited: 3
BiGRUD-SA: Protein S-sulfenylation sites prediction based on BiGRU and self-attention
Tingting Zhang, Jihua Jia, Cheng Chen, et al.
Computers in Biology and Medicine (2023) Vol. 163, pp. 107145-107145
Closed Access | Times Cited: 3
Development of an experiment-split method for benchmarking the generalization of a PTM site predictor: Lysine methylome as an example
Guoyang Zou, Yang Zou, Chenglong Ma, et al.
PLoS Computational Biology (2021) Vol. 17, Iss. 12, pp. e1009682-e1009682
Open Access | Times Cited: 7
DeepCys: Structure‐based multiple cysteine function prediction method trained on deep neural network: Case study on domains of unknown functions belonging to COX2 domains
Vamsi Nallapareddy, Shubham Rajendra Bogam, Himaja Devarakonda, et al.
Proteins Structure Function and Bioinformatics (2021) Vol. 89, Iss. 7, pp. 745-761
Closed Access | Times Cited: 6
DTL-NeddSite: A Deep-Transfer Learning Architecture for Prediction of Lysine Neddylation Sites
Deli Xu, Yafei Zhu, Qiang Xu, et al.
IEEE Access (2023) Vol. 11, pp. 51798-51809
Open Access | Times Cited: 2
Edeepsadpr: An Extensive Deep-Learning Architecture for Prediction of the in Situ Crosstalks of Serine Phosphorylation and ADP-Ribosylation
Haoqiang Jiang, Shipeng Shang, Yutong Sha, et al.
(2023)
Open Access | Times Cited: 1
SBP-SITA: A sequence-based prediction tool for S-itaconation
Laizhi Zhang, Xuanwen Wang, Lin Zhang, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2021)
Open Access | Times Cited: 2
EdeepSADPr: an extensive deep-learning architecture for prediction of the in situ crosstalks of serine phosphorylation and ADP-ribosylation
Haoqiang Jiang, Shipeng Shang, Yutong Sha, et al.
Frontiers in Cell and Developmental Biology (2023) Vol. 11
Open Access
Cysteine post-translational modifications: ten years from chemical proteomics to bioinformatics
Yanzheng Meng, Lei Li
arXiv (Cornell University) (2021)
Open Access
Page 1

Scroll to top