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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:

DeepD2V: A Novel Deep Learning-Based Framework for Predicting Transcription Factor Binding Sites from Combined DNA Sequence
Lei Deng, Hui Wu, Xuejun Liu, et al.
International Journal of Molecular Sciences (2021) Vol. 22, Iss. 11, pp. 5521-5521
Open Access | Times Cited: 24

Showing 24 citing articles:

BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification
Anderson P. Avila-Santos, Breno L. S. de Almeida, Robson Parmezan Bonidia, et al.
RNA Biology (2024) Vol. 21, Iss. 1, pp. 1-12
Open Access | Times Cited: 9
Bio-Constrained Codes with Neural Network for Density-Based DNA Data Storage
Abdur Rasool, Qiang Qu, Yang Wang, et al.
Mathematics (2022) Vol. 10, Iss. 5, pp. 845-845
Open Access | Times Cited: 20
iEnhancer-DCLA: using the original sequence to identify enhancers and their strength based on a deep learning framework
Meng Liao, Jianping Zhao, Jing Tian, et al.
BMC Bioinformatics (2022) Vol. 23, Iss. 1
Open Access | Times Cited: 14
Emvirus: An embedding-based neural framework for human-virus protein-protein interactions prediction
Pengfei Xie, Jujuan Zhuang, Geng Tian, et al.
Biosafety and Health (2023) Vol. 5, Iss. 3, pp. 152-158
Open Access | Times Cited: 7
DeepCTF: transcription factor binding specificity prediction using DNA sequence plus shape in an attention-based deep learning model
Sana Tariq, Asjad Amin
Signal Image and Video Processing (2024) Vol. 18, Iss. 6-7, pp. 5239-5251
Closed Access | Times Cited: 2
MulTFBS: A Spatial-Temporal Network with Multichannels for Predicting Transcription Factor Binding Sites
Jujuan Zhuang, Xinru Huang, Shuhan Liu, et al.
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 10, pp. 4322-4333
Closed Access | Times Cited: 1
A KAN-based hybrid deep neural networks for accurate identification of transcription factor binding sites
Guodong He, Jiahao Ye, Huijun Hao, et al.
Research Square (Research Square) (2024)
Closed Access | Times Cited: 1
BCDB: A Dual-Branch Network Based on Transformer for Predicting Transcription Factor Binding Sites
Jiaqi He, Yupeng Zhang, Yuhang Liu, et al.
Methods (2024)
Closed Access | Times Cited: 1
Pan-cancer identification of the relationship of metabolism-related differentially expressed transcription regulation with non-differentially expressed target genes via a gated recurrent unit network
Meiyu Duan, Yueying Wang, Ya Qiao, et al.
Computers in Biology and Medicine (2022) Vol. 148, pp. 105883-105883
Closed Access | Times Cited: 7
A comparative benchmark of classic DNA motif discovery tools on synthetic data
Stefano Castellana, Tommaso Biagini, Luca Parca, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 6
Closed Access | Times Cited: 6
BindTransNet: A Transferable Transformer-Based Architecture for Cross-Cell Type DNA-Protein Binding Sites Prediction
Zixuan Wang, Xiaoyao Tan, Beichen Li, et al.
Lecture notes in computer science (2021), pp. 203-214
Closed Access | Times Cited: 5
By hybrid neural networks for prediction and interpretation of transcription factor binding sites based on multi-omics
Yongqing Zhang, Zixuan Wang, Yuhang Liu, et al.
2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2021), pp. 594-599
Closed Access | Times Cited: 5
Malignancy Transcriptome Analysis, Tools and Deep Learning Methodologies for Prediction of Diseases
Asha Abraham, R. Kayalvizhi, Habeeb Shaik Mohideen, et al.
2022 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) (2022), pp. 1-11
Closed Access | Times Cited: 3
Exploring Predictive Models Utilizing Machine Learning and Deep Learning Techniques for Diabetes Mellitus: A Comprehensive Literature Review
Lena abed ALraheim Hamza, Hussein Attya Lafta, Sura Z. Al Rashid
Lecture notes in networks and systems (2024), pp. 615-631
Closed Access
Predicting CTCF’s cell type-specific binding sites in human genome
Lu Chai, Jie Gao, Zihan Li, et al.
Research Square (Research Square) (2024)
Open Access
Predicting CTCF cell type active binding sites in human genome
Lu Chai, Jie Gao, Zihan Li, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
Exploration of non-coding RNA in complex microbial communities with machine learning
Anderson P. Avila-Santos
(2024)
Open Access
Classification in Different Genera by Cytochrome Oxidase Subunit I Gene Using CNN-LSTM Hybrid Model
Meijing Li, Dong-Keun Kim
Journal of information and communication convergence engineering (2023) Vol. 21, Iss. 2, pp. 159-166
Open Access | Times Cited: 1
GNet: An integrated context-aware neural framework for transcription factor binding signal at single nucleotide resolution prediction
Jujuan Zhuang, Kexin Feng, Xinyang Teng, et al.
Mathematical Biosciences & Engineering (2023) Vol. 20, Iss. 9, pp. 15809-15829
Open Access | Times Cited: 1
TFBSnet: A deep learning-based tool for predicting transcription factor binding site from DNA sequences
Zhihua Du, Tianyou Huang, Jianqiang Li, et al.
2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2023) Vol. 23, pp. 494-499
Closed Access | Times Cited: 1
Densely Convolutional Neural Network for Transcription Factor Binding Sites Prediction Using DNA Sequence and Histone Modification
Beichen Li, Zixuan Wang, Shuwen Xiong, et al.
(2022), pp. 179-183
Closed Access | Times Cited: 1
The Effect of Numerical Mapping Techniques on Performance in Genomic Research
Seda Nur GÜLOCAK, Bihter Daş
Sakarya University Journal of Computer and Information Sciences (2022) Vol. 5, Iss. 3, pp. 315-340
Open Access | Times Cited: 1
Single-cell TF-DNA binding prediction and analysis based on transfer learning framework
Zixuan Wang, Yongqing Zhang, Yun Yu, et al.
2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2022), pp. 589-594
Closed Access | Times Cited: 1
iEnhancer-DCLA: Using the original sequence to identify enhancers and their strength based on a deep learning framework
Meng Liao, Jianping Zhao, Jing Tian, et al.
Research Square (Research Square) (2022)
Open Access
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