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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:

Systematic review of computational methods for drug combination prediction
Weikaixin Kong, Gianmarco Midena, Yingjia Chen, et al.
Computational and Structural Biotechnology Journal (2022) Vol. 20, pp. 2807-2814
Open Access | Times Cited: 34

Showing 1-25 of 34 citing articles:

Harnessing machine learning to find synergistic combinations for FDA-approved cancer drugs
Tarek Abd El‐Hafeez, Mahmoud Y. Shams, Yaseen A. M. M. Elshaier, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 34
Potentials and future perspectives of multi-target drugs in cancer treatment: the next generation anti-cancer agents
Ali Doostmohammadi, Hossein Jooya, Kimia Ghorbanian, et al.
Cell Communication and Signaling (2024) Vol. 22, Iss. 1
Open Access | Times Cited: 22
The role and potential of computer-aided drug discovery strategies in the discovery of novel antimicrobials
Samson O. Oselusi, Phumuzile Dube, Adeshina I. Odugbemi, et al.
Computers in Biology and Medicine (2024) Vol. 169, pp. 107927-107927
Open Access | Times Cited: 15
Artificial intelligence-driven drug development against autoimmune diseases
Philippe Moingeon
Trends in Pharmacological Sciences (2023) Vol. 44, Iss. 7, pp. 411-424
Open Access | Times Cited: 21
An in-depth review of AI-powered advancements in cancer drug discovery
Le Huu Nhat Minh, P Nguyen, Nguyen Thi Trang, et al.
Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease (2025), pp. 167680-167680
Closed Access
Advancing personalized cancer therapy: Onko_DrugCombScreen—a novel Shiny app for precision drug combination screening
Jingyu Yang, Meng Wang, Jürgen Dönitz, et al.
NAR Genomics and Bioinformatics (2025) Vol. 7, Iss. 1
Open Access
Predicting drug combination response surfaces
Riikka Huusari, Tianduanyi Wang, Sándor Szedmák, et al.
npj Drug Discovery. (2025) Vol. 2, Iss. 1
Open Access
Emerging Promise of Computational Techniques in Anti-Cancer Research: At a Glance
Md. Mominur Rahman, Md. Rezaul Islam, Firoza Rahman, et al.
Bioengineering (2022) Vol. 9, Iss. 8, pp. 335-335
Open Access | Times Cited: 27
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: 18
Systems Theory-Driven Framework for AI Integration into the Holistic Material Basis Research of Traditional Chinese Medicine
Jingqi Zeng, Xiao‐Bin Jia
Engineering (2024) Vol. 40, pp. 28-50
Open Access | Times Cited: 5
DrugMAP 2.0: molecular atlas and pharma-information of all drugs
Fengcheng Li, Minjie Mou, LI Xiao-yi, et al.
Nucleic Acids Research (2024) Vol. 53, Iss. D1, pp. D1372-D1382
Open Access | Times Cited: 5
Single-cell transcriptomes identify patient-tailored therapies for selective co-inhibition of cancer clones
Aleksandr Ianevski, Kristen Nader, Kyriaki Driva, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 5
The recent progress of deep-learning-based in silico prediction of drug combination
Haoyang Liu, Zhiguang Fan, Jie Lin, et al.
Drug Discovery Today (2023) Vol. 28, Iss. 7, pp. 103625-103625
Closed Access | Times Cited: 13
Integration of Pan-Cancer Cell Line and Single-Cell Transcriptomic Profiles Enables Inference of Therapeutic Vulnerabilities in Heterogeneous Tumors
Weijie Zhang, Danielle Maeser, Adam M. Lee, et al.
Cancer Research (2024) Vol. 84, Iss. 12, pp. 2021-2033
Open Access | Times Cited: 3
A network-based trans-omics approach for predicting synergistic drug combinations
Midori Iida, Yurika Kuniki, Kenta Yagi, et al.
Communications Medicine (2024) Vol. 4, Iss. 1
Open Access | Times Cited: 3
Construction of a Waddington-like landscape model that can guide clinical exploration of p53-dynamics-activating parameters in the face of divergent p53 dynamics
Gökhan Demirkıran
Communications in Nonlinear Science and Numerical Simulation (2024) Vol. 132, pp. 107893-107893
Closed Access | Times Cited: 1
Computer-aided drug discovery strategies for novel therapeutics for prostate cancer leveraging next-generating sequencing data
Weijie Zhang, R. Stephanie Huang
Expert Opinion on Drug Discovery (2024) Vol. 19, Iss. 7, pp. 841-853
Closed Access | Times Cited: 1
Combining treatments for migraine prophylaxis: the state-of-the-art
Lanfranco Pellesi, David García‐Azorín, Eloísa Rubio‐Beltrán, et al.
The Journal of Headache and Pain (2024) Vol. 25, Iss. 1
Open Access | Times Cited: 1
Machine learning–enabled virtual screening indicates the anti-tuberculosis activity of aldoxorubicin and quarfloxin with verification by molecular docking, molecular dynamics simulations, and biological evaluations
Si Zheng, Yaowen Gu, Yuzhen Gu, et al.
Briefings in Bioinformatics (2024) Vol. 26, Iss. 1
Open Access | Times Cited: 1
Computational Advancements in Cancer Combination Therapy Prediction
Victoria L. Flanary, Jennifer L. Fisher, Elizabeth J. Wilk, et al.
JCO Precision Oncology (2023), Iss. 7
Open Access | Times Cited: 4
Computational Advancements in Drug Repurposing for Cancer Combination Therapy Prediction
Victoria L. Flanary, Jennifer L. Fisher, Elizabeth J. Wilk, et al.
(2023)
Open Access | Times Cited: 3
CADD Approaches in Anticancer Drug Discovery
Abanish Biswas, Venkatesan Jayaprakash
(2023), pp. 283-311
Closed Access | Times Cited: 2
Inferring therapeutic vulnerability within tumors through integration of pan-cancer cell line and single-cell transcriptomic profiles
Weijie Zhang, Danielle Maeser, Adam F. Lee, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 2
Pathway activation model for personalized prediction of drug synergy
Quang Thinh Trac, Yue Huang, Tom Erkers, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
DVMPDC: A Deep Learning Model Based on Dual-View Representation and Multi-Strategy Pooling for Predicting Synergistic Drug Combinations
Chenliang Xie, Haochen Zhao, Jianxin Wang
Lecture notes in computer science (2024), pp. 445-457
Closed Access
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