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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:

Quantitative structure–activity relationship: promising advances in drug discovery platforms
Tao Wang, Mianbin Wu, Jianping Lin, et al.
Expert Opinion on Drug Discovery (2015) Vol. 10, Iss. 12, pp. 1283-1300
Closed Access | Times Cited: 111

Showing 1-25 of 111 citing articles:

From machine learning to deep learning: progress in machine intelligence for rational drug discovery
Lu Zhang, Jianjun Tan, Dan Han, et al.
Drug Discovery Today (2017) Vol. 22, Iss. 11, pp. 1680-1685
Closed Access | Times Cited: 654
A Review on Applications of Computational Methods in Drug Screening and Design
Xiaoqian Lin, Xiu Li, Xubo Lin
Molecules (2020) Vol. 25, Iss. 6, pp. 1375-1375
Open Access | Times Cited: 542
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: 260
Use of machine learning approaches for novel drug discovery
Angélica Nakagawa Lima, Eric Allison Philot, Gustavo Henrique Goulart Trossini, et al.
Expert Opinion on Drug Discovery (2016) Vol. 11, Iss. 3, pp. 225-239
Closed Access | Times Cited: 233
Identification of novel compounds against three targets of SARS CoV-2 coronavirus by combined virtual screening and supervised machine learning
Onat Kadioglu, Mohamed E.M. Saeed, Henry Johannes Greten, et al.
Computers in Biology and Medicine (2021) Vol. 133, pp. 104359-104359
Open Access | Times Cited: 161
Application of artificial intelligence and machine learning in early detection of adverse drug reactions (ADRs) and drug-induced toxicity
Siyun Yang, Supratik Kar
Artificial Intelligence Chemistry (2023) Vol. 1, Iss. 2, pp. 100011-100011
Open Access | Times Cited: 46
Transfer and Multi-task Learning in QSAR Modeling: Advances and Challenges
Rodolfo Simões, Vinícius Gonçalves Maltarollo, Patrícia R. Oliveira, et al.
Frontiers in Pharmacology (2018) Vol. 9
Open Access | Times Cited: 97
Advancement of multi-target drug discoveries and promising applications in the field of Alzheimer's disease
Tao Wang, Xiaohuan Liu, Jing Guan, et al.
European Journal of Medicinal Chemistry (2019) Vol. 169, pp. 200-223
Closed Access | Times Cited: 80
Explainable AI-driven prediction of APE1 inhibitors: enhancing cancer therapy with machine learning models and feature importance analysis
Aga Basit Iqbal, Tariq Masoodi, Ajaz A. Bhat, et al.
Molecular Diversity (2025)
Closed Access | Times Cited: 1
Marine natural products with anti-inflammatory activity
Randy Chi Fai Cheung, Tzi Bun Ng, Jack Ho Wong, et al.
Applied Microbiology and Biotechnology (2015) Vol. 100, Iss. 4, pp. 1645-1666
Closed Access | Times Cited: 89
Integrated Strategy for Lead Optimization Based on Fragment Growing: The Diversity-Oriented-Target-Focused-Synthesis Approach
Laurent Hoffer, Yu. V. Voitovich, Brigitt Raux, et al.
Journal of Medicinal Chemistry (2018) Vol. 61, Iss. 13, pp. 5719-5732
Open Access | Times Cited: 66
Identification of novel compounds against three targets of SARS CoV-2 coronavirus by combined virtual screening and supervised machine learning
Onat Kadioglu, Mohamed E.M. Saeed, Henry Johannes Greten, et al.
(2020)
Closed Access | Times Cited: 51
Integrated in silico formulation design of self-emulsifying drug delivery systems
Haoshi Gao, Haoyue Jia, Jie Dong, et al.
Acta Pharmaceutica Sinica B (2021) Vol. 11, Iss. 11, pp. 3585-3594
Open Access | Times Cited: 42
Artificial Intelligence: The Milestone in Modern Biomedical Research
Konstantina Athanasopoulou, Glykeria N. Daneva, Panagiotis G. Adamopoulos, et al.
BioMedInformatics (2022) Vol. 2, Iss. 4, pp. 727-744
Open Access | Times Cited: 37
Artificial intelligence in healthcare: a mastery
Jayanti Mukherjee, Ramesh Sharma, Prasenjit Dutta, et al.
Biotechnology and Genetic Engineering Reviews (2023) Vol. 40, Iss. 3, pp. 1659-1708
Closed Access | Times Cited: 21
DrugGPT: A GPT-based Strategy for Designing Potential Ligands Targeting Specific Proteins
Yuesen Li, Chengyi Gao, Xin Song, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 20
Advances, opportunities, and challenges in methods for interrogating the structure activity relationships of natural products
Christine Mae F. Ancajas, Abiodun S. Oyedele, Caitlin M. Butt, et al.
Natural Product Reports (2024) Vol. 41, Iss. 10, pp. 1543-1578
Open Access | Times Cited: 7
Artificial intelligence in antidiabetic drug discovery: The advances in QSAR and the prediction of α-glucosidase inhibitors
Adeshina I. Odugbemi, Clement N. Nyirenda, Alan Christoffels, et al.
Computational and Structural Biotechnology Journal (2024) Vol. 23, pp. 2964-2977
Open Access | Times Cited: 7
Hybridizing Feature Selection and Feature Learning Approaches in QSAR Modeling for Drug Discovery
Ignacio Ponzoni, Víctor Sebastián-Pérez, Carlos Requeña, et al.
Scientific Reports (2017) Vol. 7, Iss. 1
Open Access | Times Cited: 60
The advancement of multidimensional QSAR for novel drug discovery - where are we headed?
Tao Wang, Xinsong Yuan, Mianbin Wu, et al.
Expert Opinion on Drug Discovery (2017), pp. 1-16
Closed Access | Times Cited: 53
Discovery of Novel Antischistosomal Agents by Molecular Modeling Approaches
Ana Carolina Mafud, Leonardo L. G. Ferreira, Yvonne Primerano Mascarenhas, et al.
Trends in Parasitology (2016) Vol. 32, Iss. 11, pp. 874-886
Closed Access | Times Cited: 49
Requirements for Animal Experiments: Problems and Challenges
Flavia Fontana, Patrícia Figueiredo, João P. Martins, et al.
Small (2020) Vol. 17, Iss. 15
Closed Access | Times Cited: 48
Artificial intelligence and machine-learning approaches in structure and ligand-based discovery of drugs affecting central nervous system
Vertika Gautam, Anand Gaurav, Neeraj Masand, et al.
Molecular Diversity (2022) Vol. 27, Iss. 2, pp. 959-985
Closed Access | Times Cited: 23
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: 5
Large-Scale Prediction of Drug-Target Interaction: a Data-Centric Review
Tiejun Cheng, Ming Hao, Takako Takeda, et al.
The AAPS Journal (2017) Vol. 19, Iss. 5, pp. 1264-1275
Open Access | Times Cited: 44
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