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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:

Machine Learning Models Identify Inhibitors of SARS-CoV-2
Victor O. Gawriljuk, Phyo Phyo Kyaw Zin, Ana C. Puhl, et al.
Journal of Chemical Information and Modeling (2021) Vol. 61, Iss. 9, pp. 4224-4235
Open Access | Times Cited: 43

Showing 1-25 of 43 citing articles:

Quantum machine learning framework for virtual screening in drug discovery: a prospective quantum advantage
Stefano Mensa, Emre Sahin, Francesco Tacchino, et al.
Machine Learning Science and Technology (2023) Vol. 4, Iss. 1, pp. 015023-015023
Open Access | Times Cited: 37
Quantum Machine Learning Algorithms for Drug Discovery Applications
Kushal Batra, Kimberley M. Zorn, Daniel H. Foil, et al.
Journal of Chemical Information and Modeling (2021) Vol. 61, Iss. 6, pp. 2641-2647
Open Access | Times Cited: 92
Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2
Kaifu Gao, Rui Wang, Jiahui Chen, et al.
Chemical Reviews (2022) Vol. 122, Iss. 13, pp. 11287-11368
Open Access | Times Cited: 54
Artificial Intelligence Technologies for COVID-19 De Novo Drug Design
Giuseppe Floresta, Chiara Zagni, Davide Gentile, et al.
International Journal of Molecular Sciences (2022) Vol. 23, Iss. 6, pp. 3261-3261
Open Access | Times Cited: 39
Practical guidelines for the use of gradient boosting for molecular property prediction
Davide Boldini, Francesca Grisoni, Daniel Kühn, et al.
Journal of Cheminformatics (2023) Vol. 15, Iss. 1
Open Access | Times Cited: 20
Machine Learning-Guided Discovery of AcrB and MexB Efflux Pump Inhibitors
Abhishek Bera, Rakesh Kumar Roy, P. C. Joshi, et al.
The Journal of Physical Chemistry B (2024) Vol. 128, Iss. 3, pp. 648-663
Closed Access | Times Cited: 7
A review on computer‐aided chemogenomics and drug repositioning for rationalCOVID‐19 drug discovery
Saeid Maghsoudi, Bahareh Taghavi Shahraki, Fatemeh Rameh, et al.
Chemical Biology & Drug Design (2022) Vol. 100, Iss. 5, pp. 699-721
Open Access | Times Cited: 30
Machine Learning and Artificial Intelligence: A Paradigm Shift in Big Data-Driven Drug Design and Discovery
Purvashi Pasrija, Prakash Jha, Pruthvi Upadhyaya, et al.
Current Topics in Medicinal Chemistry (2022) Vol. 22, Iss. 20, pp. 1692-1727
Closed Access | Times Cited: 28
Uncertainty quantification: Can we trust artificial intelligence in drug discovery?
Jie Yu, Dingyan Wang, Mingyue Zheng
iScience (2022) Vol. 25, Iss. 8, pp. 104814-104814
Open Access | Times Cited: 23
Machine Learning First Response to COVID-19: A Systematic Literature Review of Clinical Decision Assistance Approaches during Pandemic Years from 2020 to 2022
Goizalde Badiola-Zabala, José Manuel López-Guede, Julián Estévez, et al.
Electronics (2024) Vol. 13, Iss. 6, pp. 1005-1005
Open Access | Times Cited: 3
Revolution of Artificial Intelligence in Computational Chemistry Breakthroughs
Anjaneyulu Bendi, Sanchita Goswami, Prithu Banik, et al.
Chemistry Africa (2024) Vol. 7, Iss. 6, pp. 3443-3459
Closed Access | Times Cited: 3
Scaffold-Retained Structure Generator to Exhaustively Create Molecules in an Arbitrary Chemical Space
Kazuma Kaitoh, Yoshihiro Yamanishi
Journal of Chemical Information and Modeling (2022) Vol. 62, Iss. 9, pp. 2212-2225
Closed Access | Times Cited: 15
Computational Approaches in the Discovery and Development of Therapeutic and Prophylactic Agents for Viral Diseases
Anand Gaurav, Neetu Agrawal, Mayasah Al‐Nema, et al.
Current Topics in Medicinal Chemistry (2022) Vol. 22, Iss. 26, pp. 2190-2206
Closed Access | Times Cited: 15
Identification of SARS-CoV-2 Main Protease Inhibitors Using Chemical Similarity Analysis Combined with Machine Learning
K. Eurídice Juárez‐Mercado, Milton Abraham Gómez-Hernández, Juana Salinas-Trujano, et al.
Pharmaceuticals (2024) Vol. 17, Iss. 2, pp. 240-240
Open Access | Times Cited: 2
Designing drugs when there is low data availability: one-shot learning and other approaches to face the issues of a long-term concern
Gabriel Corrêa Veríssimo, Mateus Sá Magalhães Serafim, Thales Kronenberger, et al.
Expert Opinion on Drug Discovery (2022) Vol. 17, Iss. 9, pp. 929-947
Closed Access | Times Cited: 13
A review of SARS-CoV-2 drug repurposing: databases and machine learning models
Marim Elkashlan, Rahaf M. Ahmad, Malak Hajar, et al.
Frontiers in Pharmacology (2023) Vol. 14
Open Access | Times Cited: 7
Knowing and combating the enemy: a brief review on SARS-CoV-2 and computational approaches applied to the discovery of drug candidates
Mateus Sá Magalhães Serafim, Jadson Castro Gertrudes, Débora Maria Abrantes Costa, et al.
Bioscience Reports (2021) Vol. 41, Iss. 3
Open Access | Times Cited: 18
Machine learning combines atomistic simulations to predict SARS-CoV-2 Mpro inhibitors from natural compounds
Trung Hai Nguyen, Quynh Mai Thai, Phạm Minh Quân, et al.
Molecular Diversity (2023) Vol. 28, Iss. 2, pp. 553-561
Open Access | Times Cited: 6
Targeting SARS-CoV-2 Main Protease: A Successful Story Guided by an In Silico Drug Repurposing Approach
Francesca Alessandra Ambrosio, Giosuè Costa, Isabella Romeo, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 11, pp. 3601-3613
Open Access | Times Cited: 6
Repurposing the Ebola and Marburg Virus Inhibitors Tilorone, Quinacrine and Pyronaridine: In vitro Activity Against SARS-CoV-2 and Potential Mechanisms
Ana C. Puhl, Ethan J. Fritch, Thomas R. Lane, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2020)
Open Access | Times Cited: 16
Computational and Experimental Approaches Identify Beta-Blockers as Potential SARS-CoV-2 Spike Inhibitors
Ana C. Puhl, Melina Mottin, Carolina Q. Sacramento, et al.
ACS Omega (2022) Vol. 7, Iss. 32, pp. 27950-27958
Open Access | Times Cited: 9
In-silico approaches for identification of compounds inhibiting SARS-CoV-2 3CL protease
Md. Zeyaullah, Nida Khan, Khursheed Muzammil, et al.
PLoS ONE (2023) Vol. 18, Iss. 4, pp. e0284301-e0284301
Open Access | Times Cited: 5
In Silico Therapeutic Study: The Next Frontier in the Fight against SARS-CoV-2 and Its Variants
Calvin R. Wei, Zarrin Basharat, Godwin C. Lang’at
Drugs and Drug Candidates (2024) Vol. 3, Iss. 1, pp. 54-69
Open Access | Times Cited: 1
Quantum kernel estimation-based quantum support vector regression
Xiaojian Zhou, Jieyao Yu, Junfan Tan, et al.
Quantum Information Processing (2024) Vol. 23, Iss. 1
Closed Access | Times Cited: 1
Potential dual inhibitors of Hexokinases and mitochondrial complex I discovered through machine learning approach
Akachukwu Ibezim, Emmanuel Onah, Sochi Chinaemerem Osigwe, et al.
Scientific African (2024) Vol. 24, pp. e02226-e02226
Open Access | Times Cited: 1
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