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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:

DNNAce: Prediction of prokaryote lysine acetylation sites through deep neural networks with multi-information fusion
Bin Yu, Zhaomin Yu, Cheng Chen, et al.
Chemometrics and Intelligent Laboratory Systems (2020) Vol. 200, pp. 103999-103999
Open Access | Times Cited: 44

Showing 1-25 of 44 citing articles:

Improving protein-protein interactions prediction accuracy using XGBoost feature selection and stacked ensemble classifier
Cheng Chen, Qingmei Zhang, Bin Yu, et al.
Computers in Biology and Medicine (2020) Vol. 123, pp. 103899-103899
Closed Access | Times Cited: 194
Biological Sequence Classification: A Review on Data and General Methods
Chunyan Ao, Shihu Jiao, Yansu Wang, et al.
Research (2022) Vol. 2022
Open Access | Times Cited: 70
Deep Learning in Proteomics
Bo Wen, Wen‐Feng Zeng, Yuxing Liao, et al.
PROTEOMICS (2020) Vol. 20, Iss. 21-22
Open Access | Times Cited: 128
Prediction of bio-sequence modifications and the associations with diseases
Chunyan Ao, Liang Yu, Quan Zou
Briefings in Functional Genomics (2020) Vol. 20, Iss. 1, pp. 1-18
Closed Access | Times Cited: 72
STALLION: a stacking-based ensemble learning framework for prokaryotic lysine acetylation site prediction
Shaherin Basith, Gwang Lee, Balachandran Manavalan
Briefings in Bioinformatics (2021) Vol. 23, Iss. 1
Open Access | Times Cited: 72
ML-FGAT: Identification of multi-label protein subcellular localization by interpretable graph attention networks and feature-generative adversarial networks
Congjing Wang, Yifei Wang, Pengju Ding, et al.
Computers in Biology and Medicine (2024) Vol. 170, pp. 107944-107944
Closed Access | Times Cited: 8
Prediction of protein crotonylation sites through LightGBM classifier based on SMOTE and elastic net
Yaning Liu, Zhaomin Yu, Cheng Chen, et al.
Analytical Biochemistry (2020) Vol. 609, pp. 113903-113903
Closed Access | Times Cited: 69
Prediction of protein-protein interaction sites through eXtreme gradient boosting with kernel principal component analysis
Xue Wang, Yaqun Zhang, Bin Yu, et al.
Computers in Biology and Medicine (2021) Vol. 134, pp. 104516-104516
Closed Access | Times Cited: 52
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
RPI-MDLStack: Predicting RNA–protein interactions through deep learning with stacking strategy and LASSO
Bin Yu, Xue Wang, Yaqun Zhang, et al.
Applied Soft Computing (2022) Vol. 120, pp. 108676-108676
Closed Access | Times Cited: 26
Prediction of protein-protein interactions based on ensemble residual convolutional neural network
Hongli Gao, Cheng Chen, Shuangyi Li, et al.
Computers in Biology and Medicine (2022) Vol. 152, pp. 106471-106471
Closed Access | Times Cited: 25
Pep-CNN: An improved convolutional neural network for predicting therapeutic peptides
Shengli Zhang, Xinjie Li
Chemometrics and Intelligent Laboratory Systems (2022) Vol. 221, pp. 104490-104490
Closed Access | Times Cited: 23
Malsite-Deep: Prediction of protein malonylation sites through deep learning and multi-information fusion based on NearMiss-2 strategy
Minghui Wang, Lili Song, Yaqun Zhang, et al.
Knowledge-Based Systems (2022) Vol. 240, pp. 108191-108191
Closed Access | Times Cited: 22
RPI-CapsuleGAN: Predicting RNA-protein interactions through an interpretable generative adversarial capsule network
Yifei Wang, Xue Wang, Cheng Chen, et al.
Pattern Recognition (2023) Vol. 141, pp. 109626-109626
Closed Access | Times Cited: 13
Analysis and review of techniques and tools based on machine learning and deep learning for prediction of lysine malonylation sites in protein sequences
Shahin Ramazi, Seyed Amir Hossein Tabatabaei, Elham Khalili, et al.
Database (2024) Vol. 2024
Open Access | Times Cited: 5
Insights on post-translational modifications in fatty liver and fibrosis progression
C. Nageswara Raju, Kavitha Sankaranarayanan
Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease (2025) Vol. 1871, Iss. 3, pp. 167659-167659
Closed Access
Accurate prediction of multi-label protein subcellular localization through multi-view feature learning with RBRL classifier
Qi Zhang, Yandan Zhang, Shan Li, et al.
Briefings in Bioinformatics (2021)
Closed Access | Times Cited: 27
Accurate Prediction of Anti-hypertensive Peptides Based on Convolutional Neural Network and Gated Recurrent unit
Hongyan Shi, Shengli Zhang
Interdisciplinary Sciences Computational Life Sciences (2022) Vol. 14, Iss. 4, pp. 879-894
Closed Access | Times Cited: 21
AntiCVP-Deep: Identify anti-coronavirus peptides between different negative datasets based on self-attention and deep learning
Yan Lu, Minghui Wang, Hongyan Zhou, et al.
Biomedical Signal Processing and Control (2024) Vol. 90, pp. 105909-105909
Closed Access | Times Cited: 4
SSE-Net: A novel network based on sequence spatial equation for Camellia sinensis lysine acetylation identification
Lichao Zhang, Xue Wang, Guosheng Gao, et al.
Computational Biology and Chemistry (2025), pp. 108442-108442
Closed Access
DeepMal: Accurate prediction of protein malonylation sites by deep neural networks
Minghui Wang, Xiaoqiang Cui, Shan Li, et al.
Chemometrics and Intelligent Laboratory Systems (2020) Vol. 207, pp. 104175-104175
Closed Access | Times Cited: 31
DeepStack-DTIs: Predicting Drug–Target Interactions Using LightGBM Feature Selection and Deep-Stacked Ensemble Classifier
Yan Zhang, Zhiwen Jiang, Cheng Chen, et al.
Interdisciplinary Sciences Computational Life Sciences (2021) Vol. 14, Iss. 2, pp. 311-330
Closed Access | Times Cited: 25
Deep Learning–Based Advances In Protein Posttranslational Modification Site and Protein Cleavage Prediction
Subash C. Pakhrin, Suresh Pokharel, Hiroto Saigo, et al.
Methods in molecular biology (2022), pp. 285-322
Closed Access | Times Cited: 16
UbiComb: A Hybrid Deep Learning Model for Predicting Plant-Specific Protein Ubiquitylation Sites
Arslan Siraj, Dae Yeong Lim, Hilal Tayara, et al.
Genes (2021) Vol. 12, Iss. 5, pp. 717-717
Open Access | Times Cited: 22
UBI-XGB: IDENTIFICATION OF UBIQUITIN PROTEINS USING MACHINE LEARNING MODEL
Sikandar Rahu, Ali Ghulam, Ali Farman, et al.
Journal of Mountain Area Research (2022) Vol. 8, pp. 14-14
Open Access | Times Cited: 14
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