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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:

Application of Machine Learning for Drug–Target Interaction Prediction
Lei Xu, Xiaoqing Ru, Rong Song
Frontiers in Genetics (2021) Vol. 12
Open Access | Times Cited: 50

Showing 26-50 of 50 citing articles:

Drug Dosage Control System Using Reinforcement Learning
P. Adi Lakshmi, Anitha Kolipakula, Sathvik Saran Atchukolu, et al.
International Journal of Innovative Science and Research Technology (IJISRT) (2024), pp. 638-645
Open Access | Times Cited: 1
Artificial intelligence-enabled discovery of a RIPK3 inhibitor with neuroprotective effects in an acute glaucoma mouse model
Xing Tu, Zixing Zou, Jiahui Li, et al.
Chinese Medical Journal (2024)
Open Access | Times Cited: 1
Predicting drug–drug interactions based on multi-view and multichannel attention deep learning
Liyu Huang, Qingfeng Chen, Wei Lan
Health Information Science and Systems (2023) Vol. 11, Iss. 1
Closed Access | Times Cited: 3
Precision Psychiatry: Machine Learning as a Tool to Find New Pharmacological Targets
João Rema, Filipa Novais, Diogo Telles‐Correia
Current Topics in Medicinal Chemistry (2021) Vol. 22, Iss. 15, pp. 1261-1269
Closed Access | Times Cited: 7
A Comprehensive Comparative Analysis of Deep Learning Based Feature Representations for Molecular Taste Prediction
Yu Song, Sihao Chang, Jing Tian, et al.
Foods (2023) Vol. 12, Iss. 18, pp. 3386-3386
Open Access | Times Cited: 2
Predicting Drug-Target Interaction (DTI) based on Machine Learning with Lasso Dimensionality Reduction and SMOTE from Protein Sequence and Drug Fingerprint
Maria Theresa F. Calangian, Vincent Peter C. Magboo
2021 International Conference on Electrical, Computer and Energy Technologies (ICECET) (2022), pp. 1-6
Closed Access | Times Cited: 3
TrustAffinity: accurate, reliable and scalable out-of-distribution protein-ligand binding affinity prediction using trustworthy deep learning
Amitesh Badkul, Li Xie, Shuo Zhang, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
A comprehensive survey of drug-target interaction analysis in allopathy and siddha medicine
Uma E, T. Mala, A. Geetha, et al.
Artificial Intelligence in Medicine (2024) Vol. 157, pp. 102986-102986
Closed Access
Enhancing drug-target interaction predictions in context of neurodegenerative diseases using bidirectional long short-term memory in male Swiss albino mice pharmaco-EEG analysis
Shahnawaz Qureshi, Syed Muhammad Zeeshan Iqbal, Asif Ameer, et al.
Heliyon (2024) Vol. 10, Iss. 21, pp. e39279-e39279
Open Access
ProtContext-DTI: Protein Contextual Representation Using Masked Language Modeling in Drug Target Interaction Prediction
Leila Baghaarabani, Parvin Razzaghi, Mennatolla Magdy Mostafa, et al.
(2024), pp. 115-121
Closed Access
A Framework for Autonomous AI-Driven Drug Discovery
Douglas W. Selinger, Tom Wall, Eleni Stylianou, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Artificial Intelligence: From Drug Discovery to Clinical Pharmacology
Paola Lecca
(2024), pp. 253-271
Closed Access
Introduction
Bruno Carpentieri, Paola Lecca
(2024), pp. 1-15
Closed Access
Comparing Regularized Logistic Regression and Stochastic Gradient Descent in Predicting Drug-Gene Interactions of Inhibitors of Apoptosis Proteins in Periodontitis
Johnisha Harris, Pradeep Kumar Yadalam, Carlos M. Ardila
Cureus (2024)
Open Access
Intensive care unit-acquired weakness: Unveiling significant risk factors and preemptive strategies through machine learning
Xiaoyu He, Yi-Huan Zhao, Qi-Quan Wan, et al.
World Journal of Clinical Cases (2024) Vol. 12, Iss. 35, pp. 6760-6763
Closed Access
Prediction of antibacterial interaction between essential oils via graph embedding approach
Hiroaki Yabuuchi, Kazuhito Hayashi, A. Shigemoto, et al.
(2023)
Open Access | Times Cited: 1
Drug-target Interaction Prediction Using Machine Learning
Mohamed R. Barkat, Sherin Moussa, Nagwa Badr
(2021) Vol. 23, pp. 480-485
Closed Access | Times Cited: 3
Molecular Sub-structural Pattern Discovery using Transformer-CNN-OMBO Algorithm for Drug-target interaction (DTI) Prediction
K. Nandhini, P. Mayilvahanan
2022 6th International Conference on Trends in Electronics and Informatics (ICOEI) (2022), pp. 241-247
Closed Access | Times Cited: 1
Bipartite graph search optimization for type II diabetes mellitus Jamu formulation using branch and bound algorithm
Wisnu Ananta Kusuma, Zulfahmi Ibnu Habibi, Muhammad Fahmi Amir, et al.
Frontiers in Pharmacology (2022) Vol. 13
Open Access | Times Cited: 1
Prediction of Drug-Target Interaction Based on Multi-Head Self-Attention
Xin Ma, Yujing Cheng
2021 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) (2022), pp. 937-940
Closed Access | Times Cited: 1
Johann Gregor Mendel: the victory of statistics over human imagination
Martina Raudenská, Tomáš Vičar, Jaromír Gumulec, et al.
European Journal of Human Genetics (2023) Vol. 31, Iss. 7, pp. 744-748
Open Access
Target identification for potential drug discovery
Saurabh Sharma, J. Kumaravel, Gurjeet Kaur, et al.
Elsevier eBooks (2023), pp. 183-196
Closed Access
Prediksi Interaksi Drug Target pada Gen Kanker Menggunakan Metode Lasso-XGBoost
Muh. Fadhil Al-Haaq Ginoga, Wisnu Ananta Kusuma, Mushthofa Mushthofa
Jurnal Teknologi Informasi dan Ilmu Komputer (2023) Vol. 10, Iss. 3, pp. 531-542
Open Access
A Comprehensive Comparative Analysis of Deep Learning based Feature Representations for Molecular Taste Prediction
Yu Song, Sihao Chang, Jing Tian, et al.
(2023)
Open Access
Mining Chemogenomic Spaces for Prediction of Drug–Target Interactions
Abhigyan Nath, Radha Chaube
Methods in molecular biology (2023), pp. 155-169
Closed Access
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