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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:

A survey on deep learning in DNA/RNA motif mining
Ying He, Zhen Shen, Qinhu Zhang, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 4
Open Access | Times Cited: 85

Showing 1-25 of 85 citing articles:

Deep learning models for disease-associated circRNA prediction: a review
Yaojia Chen, Jiacheng Wang, Chuyu Wang, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 6
Closed Access | Times Cited: 39
NeuroPred-PLM: an interpretable and robust model for neuropeptide prediction by protein language model
Lei Wang, Chen Huang, Mingxia Wang, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 2
Closed Access | Times Cited: 26
Advanced insights through systematic analysis: Mapping future research directions and opportunities for xAI in deep learning and artificial intelligence used in cybersecurity
Marek Pawlicki, Aleksandra Pawlicka, Rafał Kozik, et al.
Neurocomputing (2024) Vol. 590, pp. 127759-127759
Open Access | Times Cited: 15
Predicting viral host codon fitness and path shifting through tree-based learning on codon usage biases and genomic characteristics
Shuquan Su, Zhongran Ni, Tian Lan, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access | Times Cited: 1
Spliceator: multi-species splice site prediction using convolutional neural networks
Nicolas Scalzitti, Arnaud Kress, Romain Orhand, et al.
BMC Bioinformatics (2021) Vol. 22, Iss. 1
Open Access | Times Cited: 50
Prediction of Enhancers in DNA Sequence Data using a Hybrid CNN-DLSTM Model
Amandeep Kaur, Ajay Pal Singh Chauhan, Ashwani Kumar Aggarwal
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2022) Vol. 20, Iss. 2, pp. 1327-1336
Closed Access | Times Cited: 32
Dynamic N6‐methyladenosine RNA modification regulates peanut resistance to bacterial wilt
Kai Zhao, Zhong‐Feng Li, Yunzhuo Ke, et al.
New Phytologist (2024) Vol. 242, Iss. 1, pp. 231-246
Open Access | Times Cited: 8
Base-resolution prediction of transcription factor binding signals by a deep learning framework
Qinhu Zhang, Ying He, Siguo Wang, et al.
PLoS Computational Biology (2022) Vol. 18, Iss. 3, pp. e1009941-e1009941
Open Access | Times Cited: 23
A survey on algorithms to characterize transcription factor binding sites
Manuel Tognon, Rosalba Giugno, Luca Pinello
Briefings in Bioinformatics (2023) Vol. 24, Iss. 3
Open Access | Times Cited: 14
Learning the Regulatory Code of Gene Expression
Jan Zrimec, Filip Buric, Mariia Kokina, et al.
Frontiers in Molecular Biosciences (2021) Vol. 8
Open Access | Times Cited: 29
A novel convolution attention model for predicting transcription factor binding sites by combination of sequence and shape
Yongqing Zhang, Zixuan Wang, Yuanqi Zeng, et al.
Briefings in Bioinformatics (2021) Vol. 23, Iss. 1
Closed Access | Times Cited: 29
DCiPatho: deep cross-fusion networks for genome scale identification of pathogens
Gaofei Jiang, Jiaxuan Zhang, Yaozhong Zhang, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 4
Open Access | Times Cited: 13
Towards a better understanding of TF-DNA binding prediction from genomic features
Zixuan Wang, Meiqin Gong, Yuhang Liu, et al.
Computers in Biology and Medicine (2022) Vol. 149, pp. 105993-105993
Closed Access | Times Cited: 17
RNAdegformer: accurate prediction of mRNA degradation at nucleotide resolution with deep learning
Shujun He, Baizhen Gao, Rushant Sabnis, et al.
Briefings in Bioinformatics (2022) Vol. 24, Iss. 1
Open Access | Times Cited: 17
TSPTFBS 2.0: trans-species prediction of transcription factor binding sites and identification of their core motifs in plants
Huiling Cheng, Lifen Liu, Yuying Zhou, et al.
Frontiers in Plant Science (2023) Vol. 14
Open Access | Times Cited: 10
Genome Motif Discovery in Zika Virus: Computational Techniques and Validation Using Greedy Method
Pushpa Susant Mahapatro, Jatinderkumar R. Saini, Shraddha Vaidya
Procedia Computer Science (2025) Vol. 252, pp. 260-269
Open Access
Predicting Transcription Factor Binding Signals Based on a Novel Encoder-Decoder Framework
Siguo Wang, Zhipeng Li, Qinhu Zhang
Communications in computer and information science (2025), pp. 130-140
Closed Access
scMGCAE: A Masked Graph Cluster Autoencoder for Single-Cell RNA-Seq Clustering
Zheyu Wu, Yueyue Wang, Qinhu Zhang
Communications in computer and information science (2025), pp. 52-63
Closed Access
GINClus: RNA structural motif clustering using graph isomorphism network
Nabila Shahnaz Khan, Md Mahfuzur Rahaman, Shaojie Zhang
NAR Genomics and Bioinformatics (2025) Vol. 7, Iss. 2
Open Access
A survey on data integration for multi-omics sample clustering
Marta Lovino, Vincenzo Randazzo, Gabriele Ciravegna, et al.
Neurocomputing (2021) Vol. 488, pp. 494-508
Open Access | Times Cited: 23
Cross‐Species Prediction of Transcription Factor Binding by Adversarial Training of a Novel Nucleotide‐Level Deep Neural Network
Qinhu Zhang, Siguo Wang, Zhipeng Li, et al.
Advanced Science (2024)
Open Access | Times Cited: 3
Text Mining to Understand Disease-Causing Gene Variants
Leena Nezamuldeen, M. Saleet Jafri
Knowledge (2024) Vol. 4, Iss. 3, pp. 422-443
Open Access | Times Cited: 3
A survey of circular RNAs in complex diseases: databases, tools and computational methods
Qiu Xiao, Jianhua Dai, Jiawei Luo
Briefings in Bioinformatics (2021) Vol. 23, Iss. 1
Closed Access | Times Cited: 20
DeepCAC: a deep learning approach on DNA transcription factors classification based on multi-head self-attention and concatenate convolutional neural network
Jidong Zhang, Bo Liu, Jiahui Wu, et al.
BMC Bioinformatics (2023) Vol. 24, Iss. 1
Open Access | Times Cited: 7
Graph Neural Network and BERT Model for Antimalarial Drug Predictions Using Plasmodium Potential Targets
Medard Edmund Mswahili, Goodwill Erasmo Ndomba, Kyuri Jo, et al.
Applied Sciences (2024) Vol. 14, Iss. 4, pp. 1472-1472
Open Access | Times Cited: 2
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