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OpenAlex Citation Counts

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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:

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

Showing 11 citing articles:

Deep transformers and convolutional neural network in identifying DNA N6-methyladenine sites in cross-species genomes
Nguyen Quoc Khanh Le, Quang‐Thai Ho
Methods (2021) Vol. 204, pp. 199-206
Closed Access | Times Cited: 81
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
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
A hybrid feature extraction scheme for efficient malonylation site prediction
Ali Ghanbari Sorkhi, Jamshid Pirgazi, Vahid Ghasemi
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 7
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
TC-6mA-Pred: Prediction of DNA N6-Methyladenine Sites Using CNN with Transformer
Zeeshan Abbas, Mobeen Ur Rehman, Kil To Chong
2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2022), pp. 2506-2510
Closed Access | Times Cited: 3
iSUMO-RsFPN: A predictor for identifying lysine SUMOylation sites based on multi-features and feature pyramid networks
Zhe Lv, Xin Wei, Siqin Hu, et al.
Analytical Biochemistry (2024) Vol. 687, pp. 115460-115460
Closed Access
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
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
Bioinformatics resources for understanding RNA modifications
Jia Meng, Zhixiang Zuo, Tzong-Yi Lee, et al.
Methods (2022) Vol. 206, pp. 53-55
Closed Access
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