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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:

Recurrent Neural Network for Predicting Transcription Factor Binding Sites
Zhen Shen, Wenzheng Bao, De-Shuang Huang
Scientific Reports (2018) Vol. 8, Iss. 1
Open Access | Times Cited: 198

Showing 1-25 of 198 citing articles:

DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome
Yanrong Ji, Zhihan Zhou, Han Liu, et al.
Bioinformatics (2021) Vol. 37, Iss. 15, pp. 2112-2120
Open Access | Times Cited: 602
Artificial intelligence-based multi-omics analysis fuels cancer precision medicine
Xiujing He, Xiaowei Liu, Fengli Zuo, et al.
Seminars in Cancer Biology (2022) Vol. 88, pp. 187-200
Open Access | Times Cited: 157
Comprehensive evaluation of deep learning architectures for prediction of DNA/RNA sequence binding specificities
Ameni Trabelsi, Mohamed Chaabane, Asa Ben‐Hur
Bioinformatics (2019) Vol. 35, Iss. 14, pp. i269-i277
Open Access | Times Cited: 151
Deep learning for plant genomics and crop improvement
Hai Wang, Emre Çimen, Nisha Singh, et al.
Current Opinion in Plant Biology (2020) Vol. 54, pp. 34-41
Open Access | Times Cited: 150
Machine learning meets omics: applications and perspectives
Rufeng Li, Lixin Li, Yungang Xu, et al.
Briefings in Bioinformatics (2021) Vol. 23, Iss. 1
Closed Access | Times Cited: 121
A review of deep learning applications in human genomics using next-generation sequencing data
W. Alharbi, Mamoon Rashid
Human Genomics (2022) Vol. 16, Iss. 1
Open Access | Times Cited: 75
Harnessing genetic engineering to drive economic bioproduct production in algae
Abhishek Gupta, Kalisa Kang, Ruchi Pathania, et al.
Frontiers in Bioengineering and Biotechnology (2024) Vol. 12
Open Access | Times Cited: 20
DeepMicrobes: taxonomic classification for metagenomics with deep learning
Qiaoxing Liang, Paul W. Bible, Yu Liu, et al.
NAR Genomics and Bioinformatics (2020) Vol. 2, Iss. 1
Open Access | Times Cited: 133
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
AI applications in functional genomics
Claudia Caudai, Antonella Galizia, Filippo Geraci, et al.
Computational and Structural Biotechnology Journal (2021) Vol. 19, pp. 5762-5790
Open Access | Times Cited: 82
DeepGRN: prediction of transcription factor binding site across cell-types using attention-based deep neural networks
Chen Chen, Jie Hou, Xiaowen Shi, et al.
BMC Bioinformatics (2021) Vol. 22, Iss. 1
Open Access | Times Cited: 68
DeepLncLoc: a deep learning framework for long non-coding RNA subcellular localization prediction based on subsequence embedding
Min Zeng, Yifan Wu, Chengqian Lu, et al.
Briefings in Bioinformatics (2021) Vol. 23, Iss. 1
Open Access | Times Cited: 63
Opportunities and challenges for the computational interpretation of rare variation in clinically important genes
Gregory McInnes, Andrew G. Sharo, Megan L. Koleske, et al.
The American Journal of Human Genetics (2021) Vol. 108, Iss. 4, pp. 535-548
Open Access | Times Cited: 60
High-throughput deep learning variant effect prediction with Sequence UNET
Alistair S. Dunham, Pedro Beltrão, Mohammed AlQuraishi
Genome biology (2023) Vol. 24, Iss. 1
Open Access | Times Cited: 24
GMean—a semi-supervised GRU and K-mean model for predicting the TF binding site
Chuah Chai Wen, Wanxian He, De-Shuang Huang
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 10
A low-cost vision system based on the analysis of motor features for recognition and severity rating of Parkinson’s Disease
Domenico Buongiorno, Ilaria Bortone, Giacomo Donato Cascarano, et al.
BMC Medical Informatics and Decision Making (2019) Vol. 19, Iss. S9
Open Access | Times Cited: 76
Deep learning for inferring transcription factor binding sites
Peter K. Koo, Matt Ploenzke
Current Opinion in Systems Biology (2020) Vol. 19, pp. 16-23
Open Access | Times Cited: 67
Enhancing the interpretability of transcription factor binding site prediction using attention mechanism
Sung‐Joon Park, Yookyung Koh, Hwisang Jeon, et al.
Scientific Reports (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 63
DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome
Yanrong Ji, Zhihan Zhou, Han Liu, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2020)
Open Access | Times Cited: 49
DeepDRBP-2L: A New Genome Annotation Predictor for Identifying DNA-Binding Proteins and RNA-Binding Proteins Using Convolutional Neural Network and Long Short-Term Memory
Jun Zhang, Qingcai Chen, Bin Liu
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2019) Vol. 18, Iss. 4, pp. 1451-1463
Closed Access | Times Cited: 44
SAResNet: self-attention residual network for predicting DNA-protein binding
Long-Chen Shen, Yan Liu, Jiangning Song, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 5
Open Access | Times Cited: 41
Sequence-based peptide identification, generation, and property prediction with deep learning: a review
Xumin Chen, Chen Li, Matthew T. Bernards, et al.
Molecular Systems Design & Engineering (2021) Vol. 6, Iss. 6, pp. 406-428
Closed Access | Times Cited: 36
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
Advances in stress-tolerance elements for microbial cell factories
Zheyi Kuang, Xiaofang Yan, Yanfei Yuan, et al.
Synthetic and Systems Biotechnology (2024) Vol. 9, Iss. 4, pp. 793-808
Open Access | Times Cited: 6
Proformer: a hybrid macaron transformer model predicts expression values from promoter sequences
Il‐Youp Kwak, Byeongchan Kim, Juhyun Lee, et al.
BMC Bioinformatics (2024) Vol. 25, Iss. 1
Open Access | Times Cited: 5
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