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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:

Deep4mC: systematic assessment and computational prediction for DNA N4-methylcytosine sites by deep learning
Haodong Xu, Peilin Jia, Zhongming Zhao
Briefings in Bioinformatics (2020) Vol. 22, Iss. 3
Open Access | Times Cited: 72

Showing 1-25 of 72 citing articles:

iLearnPlus:a comprehensive and automated machine-learning platform for nucleic acid and protein sequence analysis, prediction and visualization
Zhen Chen, Pei Zhao, Chen Li, et al.
Nucleic Acids Research (2021) Vol. 49, Iss. 10, pp. e60-e60
Open Access | Times Cited: 194
BERT4Bitter: a bidirectional encoder representations from transformers (BERT)-based model for improving the prediction of bitter peptides
Phasit Charoenkwan, Chanin Nantasenamat, Md Mehedi Hasan, et al.
Bioinformatics (2021) Vol. 37, Iss. 17, pp. 2556-2562
Closed Access | Times Cited: 134
Deep-Kcr: accurate detection of lysine crotonylation sites using deep learning method
Hao Lv, Fanny Dao, Zheng-Xing Guan, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 4
Closed Access | Times Cited: 112
Analysis of DNA Sequence Classification Using CNN and Hybrid Models
Hemalatha Gunasekaran, K. Ramalakshmi, A. Rex Macedo Arokiaraj, et al.
Computational and Mathematical Methods in Medicine (2021) Vol. 2021, pp. 1-12
Open Access | Times Cited: 88
iFeatureOmega:an integrative platform for engineering, visualization and analysis of features from molecular sequences, structural and ligand data sets
Zhen Chen, Xuhan Liu, Pei Zhao, et al.
Nucleic Acids Research (2022) Vol. 50, Iss. W1, pp. W434-W447
Open Access | Times Cited: 57
iDNA-OpenPrompt: OpenPrompt learning model for identifying DNA methylation
Xia Yu, Jia Ren, Haixia Long, et al.
Frontiers in Genetics (2024) Vol. 15
Open Access | Times Cited: 11
A deep multiple kernel learning-based higher-order fuzzy inference system for identifying DNA N4-methylcytosine sites
Leyao Wang, Yijie Ding, Prayag Tiwari, et al.
Information Sciences (2023) Vol. 630, pp. 40-52
Closed Access | Times Cited: 19
4mCBERT: A computing tool for the identification of DNA N4-methylcytosine sites by sequence- and chemical-derived information based on ensemble learning strategies
Sen Yang, Zexi Yang, Jun Yang
International Journal of Biological Macromolecules (2023) Vol. 231, pp. 123180-123180
Closed Access | Times Cited: 16
DeepSF-4mC: A deep learning model for predicting DNA cytosine 4mC methylation sites leveraging sequence features
Zhaomin Yao, Fei Li, Weiming Xie, et al.
Computers in Biology and Medicine (2024) Vol. 171, pp. 108166-108166
Open Access | Times Cited: 6
Using a hybrid neural network architecture for DNA sequence representation: A study on N4-methylcytosine sites
Van-Nui Nguyen, Trang-Thi Ho, Thu-Dung Doan, et al.
Computers in Biology and Medicine (2024) Vol. 178, pp. 108664-108664
Closed Access | Times Cited: 6
Empirical Comparison and Analysis of Web-Based DNA N4-Methylcytosine Site Prediction Tools
Balachandran Manavalan, Md Mehedi Hasan, Shaherin Basith, et al.
Molecular Therapy — Nucleic Acids (2020) Vol. 22, pp. 406-420
Open Access | Times Cited: 44
iDNA-ABT: advanced deep learning model for detecting DNA methylation with adaptive features and transductive information maximization
Yingying Yu, Wenjia He, Junru Jin, et al.
Bioinformatics (2021) Vol. 37, Iss. 24, pp. 4603-4610
Closed Access | Times Cited: 36
Hyb4mC: a hybrid DNA2vec-based model for DNA N4-methylcytosine sites prediction
Ying Liang, Yanan Wu, Zequn Zhang, et al.
BMC Bioinformatics (2022) Vol. 23, Iss. 1
Open Access | Times Cited: 22
LightGBM-LncLoc: A LightGBM-Based Computational Predictor for Recognizing Long Non-Coding RNA Subcellular Localization
Jianyi Lyu, Peijie Zheng, Yue Qi, et al.
Mathematics (2023) Vol. 11, Iss. 3, pp. 602-602
Open Access | Times Cited: 15
Identifying DNA N4-methylcytosine sites in the rosaceae genome with a deep learning model relying on distributed feature representation
Jhabindra Khanal, Hilal Tayara, Quan Zou, et al.
Computational and Structural Biotechnology Journal (2021) Vol. 19, pp. 1612-1619
Open Access | Times Cited: 28
4mCPred-CNN—Prediction of DNA N4-Methylcytosine in the Mouse Genome Using a Convolutional Neural Network
Zeeshan Abbas, Hilal Tayara, Kil To Chong
Genes (2021) Vol. 12, Iss. 2, pp. 296-296
Open Access | Times Cited: 27
MuLan-Methyl—multiple transformer-based language models for accurate DNA methylation prediction
Wenhuan Zeng, Anupam Gautam, Daniel H. Huson
GigaScience (2022) Vol. 12
Open Access | Times Cited: 19
Deep learning‐enabled discovery and characterization of HKT genes in Spartina alterniflora
Maogeng Yang, Shoukun Chen, Zhangping Huang, et al.
The Plant Journal (2023) Vol. 116, Iss. 3, pp. 690-705
Open Access | Times Cited: 10
EpiTEAmDNA: Sequence feature representation via transfer learning and ensemble learning for identifying multiple DNA epigenetic modification types across species
Fei Li, Shuai Liu, Kewei Li, et al.
Computers in Biology and Medicine (2023) Vol. 160, pp. 107030-107030
Closed Access | Times Cited: 9
O-GlcNAcPRED-DL: Prediction of Protein O-GlcNAcylation Sites Based on an Ensemble Model of Deep Learning
Fengzhu Hu, Weiyu Li, Yaoxiang Li, et al.
Journal of Proteome Research (2023) Vol. 23, Iss. 1, pp. 95-106
Closed Access | Times Cited: 9
NetBCE: An Interpretable Deep Neural Network for Accurate Prediction of Linear B-Cell Epitopes
Haodong Xu, Zhongming Zhao
Genomics Proteomics & Bioinformatics (2022) Vol. 20, Iss. 5, pp. 1002-1012
Open Access | Times Cited: 14
iPro-GAN: A novel model based on generative adversarial learning for identifying promoters and their strength
Huijuan Qiao, Shengli Zhang, Tian Xue, et al.
Computer Methods and Programs in Biomedicine (2022) Vol. 215, pp. 106625-106625
Closed Access | Times Cited: 13
DNA-MP: a generalized DNA modifications predictor for multiple species based on powerful sequence encoding method
Muhammad Nabeel Asim, Muhammad Ali Ibrahim, Ahtisham Fazeel, et al.
Briefings in Bioinformatics (2022) Vol. 24, Iss. 1
Open Access | Times Cited: 13
MGF6mARice: prediction of DNA N6-methyladenine sites in rice by exploiting molecular graph feature and residual block
Mengya Liu, Zhan-Li Sun, Zhigang Zeng, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 3
Closed Access | Times Cited: 12
Systematic Analysis and Accurate Identification of DNA N4-Methylcytosine Sites by Deep Learning
Lezheng Yu, Yonglin Zhang, Xue Li, et al.
Frontiers in Microbiology (2022) Vol. 13
Open Access | Times Cited: 12
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