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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:

Advancing Drug Discovery via Artificial Intelligence
H. C. Stephen Chan, Hanbin Shan, Thamani Dahoun, et al.
Trends in Pharmacological Sciences (2019) Vol. 40, Iss. 8, pp. 592-604
Closed Access | Times Cited: 476

Showing 1-25 of 476 citing articles:

Artificial intelligence in drug discovery and development
Debleena Paul, Gaurav Sanap, Snehal Shenoy, et al.
Drug Discovery Today (2020) Vol. 26, Iss. 1, pp. 80-93
Open Access | Times Cited: 953
Artificial intelligence to deep learning: machine intelligence approach for drug discovery
Rohan Gupta, Devesh Srivastava, Mehar Sahu, et al.
Molecular Diversity (2021) Vol. 25, Iss. 3, pp. 1315-1360
Open Access | Times Cited: 812
DrugBank 6.0: the DrugBank Knowledgebase for 2024
Craig Knox, Michael Wilson, Christen M. Klinger, et al.
Nucleic Acids Research (2023) Vol. 52, Iss. D1, pp. D1265-D1275
Open Access | Times Cited: 300
Machine Learning Methods in Drug Discovery
Lauv Patel, Tripti Shukla, Xiuzhen Huang, et al.
Molecules (2020) Vol. 25, Iss. 22, pp. 5277-5277
Open Access | Times Cited: 293
Accelerated antimicrobial discovery via deep generative models and molecular dynamics simulations
Payel Das, Tom Sercu, Kahini Wadhawan, et al.
Nature Biomedical Engineering (2021) Vol. 5, Iss. 6, pp. 613-623
Open Access | Times Cited: 283
Predicting drug–disease associations through layer attention graph convolutional network
Zhouxin Yu, Feng Huang, Xiaohan Zhao, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 4
Closed Access | Times Cited: 263
Discovering Anti-Cancer Drugs via Computational Methods
Wenqiang Cui, Adnane Aouidate, Shouguo Wang, et al.
Frontiers in Pharmacology (2020) Vol. 11
Open Access | Times Cited: 240
Artificial intelligence and machine learning‐aided drug discovery in central nervous system diseases: State‐of‐the‐arts and future directions
Sezen Vatansever, Avner Schlessinger, Daniel Wacker, et al.
Medicinal Research Reviews (2020) Vol. 41, Iss. 3, pp. 1427-1473
Open Access | Times Cited: 240
New opportunities and challenges of natural products research: When target identification meets single-cell multiomics
Yuyu Zhu, Z. W. Ouyang, Haojie Du, et al.
Acta Pharmaceutica Sinica B (2022) Vol. 12, Iss. 11, pp. 4011-4039
Open Access | Times Cited: 232
Advances in De Novo Drug Design: From Conventional to Machine Learning Methods
Varnavas D. Mouchlis, Antreas Afantitis, Angela Serra, et al.
International Journal of Molecular Sciences (2021) Vol. 22, Iss. 4, pp. 1676-1676
Open Access | Times Cited: 229
Drawbacks of Artificial Intelligence and Their Potential Solutions in the Healthcare Sector
Bangul Khan, Hajira Fatima, Ayatullah Qureshi, et al.
Deleted Journal (2023) Vol. 1, Iss. 2, pp. 731-738
Open Access | Times Cited: 228
Machine learning applications in drug development
Clémence Réda, Emilie Kaufmann, Andrée Delahaye‐Duriez
Computational and Structural Biotechnology Journal (2019) Vol. 18, pp. 241-252
Open Access | Times Cited: 197
Blockchain and artificial intelligence technology in e-Health
Priti Tagde, Sandeep Tagde, Tanima Bhattacharya, et al.
Environmental Science and Pollution Research (2021) Vol. 28, Iss. 38, pp. 52810-52831
Open Access | Times Cited: 155
Exploring different approaches to improve the success of drug discovery and development projects: a review
Geoffrey Kabue Kiriiri, Peter Njogu, Alex Mwangi
Future Journal of Pharmaceutical Sciences (2020) Vol. 6, Iss. 1
Open Access | Times Cited: 148
High-Throughput Screening Platforms in the Discovery of Novel Drugs for Neurodegenerative Diseases
Hasan Aldewachi, Radhwan Nidal Al-Zidan, Matthew T. Conner, et al.
Bioengineering (2021) Vol. 8, Iss. 2, pp. 30-30
Open Access | Times Cited: 143
Graph neural networks for automated de novo drug design
Jiacheng Xiong, Zhaoping Xiong, Kaixian Chen, et al.
Drug Discovery Today (2021) Vol. 26, Iss. 6, pp. 1382-1393
Closed Access | Times Cited: 134
Artificial Intelligence and Machine Learning Technology Driven Modern Drug Discovery and Development
Chayna Sarkar, Biswadeep Das, Vikram Singh Rawat, et al.
International Journal of Molecular Sciences (2023) Vol. 24, Iss. 3, pp. 2026-2026
Open Access | Times Cited: 125
Taking the leap between analytical chemistry and artificial intelligence: A tutorial review
Lucas B. Ayres, Federico J.V. Gómez, Jeb R. Linton, et al.
Analytica Chimica Acta (2021) Vol. 1161, pp. 338403-338403
Closed Access | Times Cited: 124
Machine Learning for Biologics: Opportunities for Protein Engineering, Developability, and Formulation
Harini Narayanan, Fabian Dingfelder, Alessandro Butté, et al.
Trends in Pharmacological Sciences (2021) Vol. 42, Iss. 3, pp. 151-165
Closed Access | Times Cited: 118
Advancing pharmacy and healthcare with virtual digital technologies
Sarah J. Trenfield, Atheer Awad, Laura E. McCoubrey, et al.
Advanced Drug Delivery Reviews (2022) Vol. 182, pp. 114098-114098
Open Access | Times Cited: 117
Generative chemistry: drug discovery with deep learning generative models
Yuemin Bian, Xiang‐Qun Xie
Journal of Molecular Modeling (2021) Vol. 27, Iss. 3
Open Access | Times Cited: 108
Artificial intelligence and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries
Chandrabose Selvaraj, Ishwar Chandra, Sanjeev Kumar Singh
Molecular Diversity (2021) Vol. 26, Iss. 3, pp. 1893-1913
Open Access | Times Cited: 108
Artificial intelligence and machine learning in drug discovery and development
Veer J. Patel, Manan Shah
Intelligent Medicine (2021) Vol. 2, Iss. 3, pp. 134-140
Open Access | Times Cited: 106
Intelligent Computing: The Latest Advances, Challenges, and Future
Shiqiang Zhu, Ting Yu, Tao Xu, et al.
Intelligent Computing (2023) Vol. 2
Open Access | Times Cited: 104
Comprehensive strategies of machine-learning-based quantitative structure-activity relationship models
Jiashun Mao, Javed Akhtar, Xiao Zhang, et al.
iScience (2021) Vol. 24, Iss. 9, pp. 103052-103052
Open Access | Times Cited: 100
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