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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 in drug discovery: an integrative review and future challenges
Heba Askr, Enas Elgeldawi, Heba Aboul Ella, et al.
Artificial Intelligence Review (2022) Vol. 56, Iss. 7, pp. 5975-6037
Open Access | Times Cited: 182

Showing 1-25 of 182 citing articles:

Artificial Intelligence (AI) Applications in Drug Discovery and Drug Delivery: Revolutionizing Personalized Medicine
Dolores R. Serrano, Francis C. Luciano, Brayan J. Anaya, et al.
Pharmaceutics (2024) Vol. 16, Iss. 10, pp. 1328-1328
Open Access | Times Cited: 42
History of Artificial Intelligence
Alberto Guizzi, Patrick J. Denard, Philippe Collin, et al.
(2024), pp. 1-9
Closed Access | Times Cited: 29
Revolutionizing Drug Discovery: A Comprehensive Review of AI Applications
Rushikesh Dhudum, Ankit Ganeshpurkar, Atmaram Pawar
Drugs and Drug Candidates (2024) Vol. 3, Iss. 1, pp. 148-171
Open Access | Times Cited: 25
Explainable Artificial Intelligence for Drug Discovery and Development: A Comprehensive Survey
Roohallah Alizadehsani, Solomon Sunday Oyelere, Sadiq Hussain, et al.
IEEE Access (2024) Vol. 12, pp. 35796-35812
Open Access | Times Cited: 23
Explainable artificial intelligence: A survey of needs, techniques, applications, and future direction
Melkamu Mersha, Khang Nhứt Lâm, Joseph Wood, et al.
Neurocomputing (2024) Vol. 599, pp. 128111-128111
Closed Access | Times Cited: 20
Artificial intelligence in metabolomics: a current review
Jinhua Chi, Jingmin Shu, Ming Li, et al.
TrAC Trends in Analytical Chemistry (2024) Vol. 178, pp. 117852-117852
Closed Access | Times Cited: 17
Artificial intelligence streamlines scientific discovery of drug–target interactions
Yuxin Yang, Feixiong Cheng
British Journal of Pharmacology (2025)
Open Access | Times Cited: 2
Artificial Intelligence in Drug Discovery and Development
Kit‐Kay Mak, Yi-Hang Wong, Mallikarjuna Rao Pichika
Springer eBooks (2023), pp. 1-38
Closed Access | Times Cited: 35
Artificial Intelligence in Drug Discovery and Development
Kit‐Kay Mak, Yi-Hang Wong, Mallikarjuna Rao Pichika
Springer eBooks (2024), pp. 1461-1498
Closed Access | Times Cited: 13
Protein subcellular localization prediction tools
Maryam Gillani, Gianluca Pollastri
Computational and Structural Biotechnology Journal (2024) Vol. 23, pp. 1796-1807
Open Access | Times Cited: 12
Artificial intelligence in Immuno-genetics
Raed Farzan
Bioinformation (2024) Vol. 20, Iss. 1, pp. 29-35
Open Access | Times Cited: 11
Precision medicine in colorectal cancer: Leveraging multi-omics, spatial omics, and artificial intelligence
Zishan Xu, Wei Li, Xiangyang Dong, et al.
Clinica Chimica Acta (2024) Vol. 559, pp. 119686-119686
Closed Access | Times Cited: 11
The Artificial Intelligence-Powered New Era in Pharmaceutical Research and Development: A Review
Phuvamin Suriyaamporn, Boonnada Pamornpathomkul, Prasopchai Patrojanasophon, et al.
AAPS PharmSciTech (2024) Vol. 25, Iss. 6
Closed Access | Times Cited: 11
Large language models in bioinformatics: applications and perspectives
Jiajia Liu, Mengyuan Yang, Yankai Yu, et al.
arXiv (Cornell University) (2024)
Open Access | Times Cited: 10
Unlocking the black box: an in-depth review on interpretability, explainability, and reliability in deep learning
Emrullah Şahin, Naciye Nur Arslan, Durmuş Özdemir
Neural Computing and Applications (2024)
Closed Access | Times Cited: 10
A Comprehensive Review of Deep Learning: Architectures, Recent Advances, and Applications
Ibomoiye Domor Mienye, Theo G. Swart
Information (2024) Vol. 15, Iss. 12, pp. 755-755
Open Access | Times Cited: 10
The changing scenario of drug discovery using AI to deep learning: Recent advancement, success stories, collaborations, and challenges
Chiranjib Chakraborty, Manojit Bhattacharya, Sang‐Soo Lee, et al.
Molecular Therapy — Nucleic Acids (2024) Vol. 35, Iss. 3, pp. 102295-102295
Open Access | Times Cited: 8
Revolutionizing adjuvant development: harnessing AI for next-generation cancer vaccines
Wei Zhang, Xiaoli Zheng, Paolo Coghi, et al.
Frontiers in Immunology (2024) Vol. 15
Open Access | Times Cited: 8
Advancing paleontology: a survey on deep learning methodologies in fossil image analysis
Mohammed Yaqoob Ansari, Mohammed Ishaq Mohammed, Mohammed Yusuf Ansari, et al.
Artificial Intelligence Review (2025) Vol. 58, Iss. 3
Open Access | Times Cited: 1
Researching public health datasets in the era of deep learning: a systematic literature review
Rand Obeidat, Izzat Alsmadi, Qanita Bani Baker, et al.
Health Informatics Journal (2025) Vol. 31, Iss. 1
Open Access | Times Cited: 1
A Review on the Recent Applications of Deep Learning in Predictive Drug Toxicological Studies
Krishnendu Sinha, Nabanita Ghosh, Parames C. Sil
Chemical Research in Toxicology (2023) Vol. 36, Iss. 8, pp. 1174-1205
Closed Access | Times Cited: 22
Quinolines and isoquinolines as HIV-1 inhibitors: Chemical structures, action targets, and biological activities
Sha Hu, Jiong Chen, Jin-Xu Cao, et al.
Bioorganic Chemistry (2023) Vol. 136, pp. 106549-106549
Closed Access | Times Cited: 21
A Systematic Review of Deep Learning Methodologies Used in the Drug Discovery Process with Emphasis on In Vivo Validation
Nikoletta-Maria Koutroumpa, Konstantinos D. Papavasileiou, Anastasios G. Papadiamantis, et al.
International Journal of Molecular Sciences (2023) Vol. 24, Iss. 7, pp. 6573-6573
Open Access | Times Cited: 19
Smart Implementation of Industrial Internet of Things Using Embedded Mechatronic System
Abdelhamid Zaïdi, Ismail Keshta, Zatin Gupta, et al.
IEEE Embedded Systems Letters (2023) Vol. 16, Iss. 2, pp. 190-193
Closed Access | Times Cited: 19
An extensive survey on the use of supervised machine learning techniques in the past two decades for prediction of drug side effects
Pranab Das, Dilwar Hussain Mazumder
Artificial Intelligence Review (2023) Vol. 56, Iss. 9, pp. 9809-9836
Open Access | Times Cited: 18
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