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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:

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

Showing 13 citing articles:

Improved Prediction Model of Protein Lysine Crotonylation Sites Using Bidirectional Recurrent Neural Networks
Sian Soo Tng, Nguyen Quoc Khanh Le, Hui‐Yuan Yeh, et al.
Journal of Proteome Research (2021) Vol. 21, Iss. 1, pp. 265-273
Closed Access | Times Cited: 54
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
iKcr_CNN: A novel computational tool for imbalance classification of human nonhistone crotonylation sites based on convolutional neural networks with focal loss
Lijun Dou, Zilong Zhang, Lei Xu, et al.
Computational and Structural Biotechnology Journal (2022) Vol. 20, pp. 3268-3279
Open Access | Times Cited: 13
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
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
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
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
Word embeddings for protein sequence analysis
Ana Marta Sequeira, Iván Marcelo Gomes, Miguel Rocha
(2023), pp. 1-8
Closed 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
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