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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:

Deep learning for mining protein data
Qiang Shi, Weiya Chen, Siqi Huang, et al.
Briefings in Bioinformatics (2019) Vol. 22, Iss. 1, pp. 194-218
Closed Access | Times Cited: 67

Showing 1-25 of 67 citing articles:

MolAICal: a soft tool for 3D drug design of protein targets by artificial intelligence and classical algorithm
Qifeng Bai, Shuoyan Tan, Tingyang Xu, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 3
Open Access | Times Cited: 223
Transformer-based deep learning for predicting protein properties in the life sciences
Abel Chandra, Laura Tünnermann, Tommy Löfstedt, et al.
eLife (2023) Vol. 12
Open Access | Times Cited: 90
Using deep neural networks and biological subwords to detect protein S-sulfenylation sites
Duyen Thi, Thanh Quynh Trang Le, Nguyen Quoc Khanh Le
Briefings in Bioinformatics (2020) Vol. 22, Iss. 3
Closed Access | Times Cited: 84
Artificial Intelligence in Drug Discovery: A Comprehensive Review of Data-driven and Machine Learning Approaches
Hyunho Kim, Eun‐Young Kim, Ingoo Lee, et al.
Biotechnology and Bioprocess Engineering (2020) Vol. 25, Iss. 6, pp. 895-930
Open Access | Times Cited: 81
XGraphBoost: Extracting Graph Neural Network-Based Features for a Better Prediction of Molecular Properties
Daiguo Deng, Xiaowei Chen, Ruochi Zhang, et al.
Journal of Chemical Information and Modeling (2021) Vol. 61, Iss. 6, pp. 2697-2705
Closed Access | Times Cited: 70
PFmulDL: a novel strategy enabling multi-class and multi-label protein function annotation by integrating diverse deep learning methods
Weiqi Xia, Lingyan Zheng, Jiebin Fang, et al.
Computers in Biology and Medicine (2022) Vol. 145, pp. 105465-105465
Closed Access | Times Cited: 59
Matrikines as mediators of tissue remodelling
Nathan Jariwala, Matiss Ozols, Mike Bell, et al.
Advanced Drug Delivery Reviews (2022) Vol. 185, pp. 114240-114240
Open Access | Times Cited: 58
Omics-based deep learning approaches for lung cancer decision-making and therapeutics development
Thi-Oanh Tran, Thanh Hoa Vo, Nguyen Quoc Khanh Le
Briefings in Functional Genomics (2023) Vol. 23, Iss. 3, pp. 181-192
Closed Access | Times Cited: 26
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: 25
Struct2Graph: a graph attention network for structure based predictions of protein–protein interactions
Mayank Baranwal, Abram Magner, Jacob C. Saldinger, et al.
BMC Bioinformatics (2022) Vol. 23, Iss. 1
Open Access | Times Cited: 33
Persistent spectral based ensemble learning (PerSpect-EL) for protein–protein binding affinity prediction
JunJie Wee, Kelin Xia
Briefings in Bioinformatics (2022) Vol. 23, Iss. 2
Closed Access | Times Cited: 31
nhKcr: a new bioinformatics tool for predicting crotonylation sites on human nonhistone proteins based on deep learning
Yongzi Chen, Zhuozhi Wang, Yanan Wang, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 6
Open Access | Times Cited: 39
Mapping the glycosyltransferase fold landscape using interpretable deep learning
Rahil Taujale, Zhongliang Zhou, Wayland Yeung, et al.
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 39
DeepGOWeb: fast and accurate protein function prediction on the (Semantic) Web
Maxat Kulmanov, Fernando Zhapa-Camacho, Robert Hoehndorf
Nucleic Acids Research (2021) Vol. 49, Iss. W1, pp. W140-W146
Open Access | Times Cited: 35
Machine and deep learning to predict viral fusion peptides
Ana Marta Sequeira, Miguel Rocha, Diana Lousa
Computational and Structural Biotechnology Journal (2025) Vol. 27, pp. 692-704
Open Access
Protein pKa Prediction with Machine Learning
Zhitao Cai, Fangfang Luo, Yongxian Wang, et al.
ACS Omega (2021) Vol. 6, Iss. 50, pp. 34823-34831
Open Access | Times Cited: 29
Differences in ligand-induced protein dynamics extracted from an unsupervised deep learning approach correlate with protein–ligand binding affinities
Ikki Yasuda, Katsuhiro Endo, Eiji Yamamoto, et al.
Communications Biology (2022) Vol. 5, Iss. 1
Open Access | Times Cited: 18
Predicting Proteolysis in Complex Proteomes Using Deep Learning
Matiss Ozols, Alexander Eckersley, Christopher I. Platt, et al.
International Journal of Molecular Sciences (2021) Vol. 22, Iss. 6, pp. 3071-3071
Open Access | Times Cited: 21
PIPENN: protein interface prediction from sequence with an ensemble of neural nets
Bas Stringer, Hans de Ferrante, Sanne Abeln, et al.
Bioinformatics (2022) Vol. 38, Iss. 8, pp. 2111-2118
Open Access | Times Cited: 15
VHH Structural Modelling Approaches: A Critical Review
Poonam Vishwakarma, Akhila Melarkode Vattekatte, Nicolas K. Shinada, et al.
International Journal of Molecular Sciences (2022) Vol. 23, Iss. 7, pp. 3721-3721
Open Access | Times Cited: 15
Improving the topology prediction of α-helical transmembrane proteins with deep transfer learning
Lei Wang, Haolin Zhong, Zhidong Xue, et al.
Computational and Structural Biotechnology Journal (2022) Vol. 20, pp. 1993-2000
Open Access | Times Cited: 14
ProPythia: A Python package for protein classification based on machine and deep learning
Ana Marta Sequeira, Diana Lousa, Miguel Rocha
Neurocomputing (2021) Vol. 484, pp. 172-182
Closed Access | Times Cited: 19
Hom-Complex-Based Machine Learning (HCML) for the Prediction of Protein–Protein Binding Affinity Changes upon Mutation
Xiang Liu, Huitao Feng, Jie Wu, et al.
Journal of Chemical Information and Modeling (2022) Vol. 62, Iss. 17, pp. 3961-3969
Closed Access | Times Cited: 13
Neural networks for protein structure and function prediction and dynamic analysis
Yuko Tsuchiya, Kentaro Tomii
Biophysical Reviews (2020) Vol. 12, Iss. 2, pp. 569-573
Open Access | Times Cited: 18
Hierarchical deep learning for predicting GO annotations by integrating protein knowledge
Gabriela Merino, Rabie Saidi, Diego H. Milone, et al.
Bioinformatics (2022) Vol. 38, Iss. 19, pp. 4488-4496
Open Access | Times Cited: 12
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