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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:

Comparison of various methods for validity evaluation of QSAR models
Shadi Shayanfar, Ali Shayanfar
BMC Chemistry (2022) Vol. 16, Iss. 1
Open Access | Times Cited: 22

Showing 22 citing articles:

Recent Advances in Machine-Learning-Based Chemoinformatics: A Comprehensive Review
Sarfaraz K. Niazi, Zamara Mariam
International Journal of Molecular Sciences (2023) Vol. 24, Iss. 14, pp. 11488-11488
Open Access | Times Cited: 42
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: 18
Design, 3D-QSAR, molecular docking, ADMET, molecular dynamics and MM-PBSA simulations for new anti-breast cancer agents
Said El Rhabori, Marwa Alaqarbeh, Abdellah El Aissouq, et al.
Chemical Physics Impact (2024) Vol. 8, pp. 100455-100455
Open Access | Times Cited: 13
QSAR and machine learning-driven proposition of novel 1,3,4-oxadiazoles and structure-based studies of their antibacterial activities against Xanthomonas oryzae
Ingrid V. Pereira de Faria, A. Mesquita, Elaine F. F. da Cunha, et al.
Theoretical Chemistry Accounts (2025) Vol. 144, Iss. 2
Closed Access
Copper pyrazole complexes as potential anticancer agents: Evaluation of cytotoxic response against cancer cells and their mechanistic action at the molecular level
Monireh Ghorbanpour, Ali Shayanfar, Behzad Soltani
Coordination Chemistry Reviews (2023) Vol. 498, pp. 215459-215459
Closed Access | Times Cited: 19
Machine learning-based q-RASAR approach for the in silico identification of novel multi-target inhibitors against Alzheimer's disease
Vinay Kumar, Arkaprava Banerjee, Kunal Roy
Chemometrics and Intelligent Laboratory Systems (2023) Vol. 245, pp. 105049-105049
Closed Access | Times Cited: 14
The importance of good practices and false hits for QSAR-driven virtual screening real application: a SARS-CoV-2 main protease (Mpro) case study
Mateus Sá Magalhães Serafim, Simone Queiroz Pantaleão, Elany Barbosa da Silva, et al.
Frontiers in Drug Discovery (2023) Vol. 3
Open Access | Times Cited: 6
2,4,6-Trimethoxy chalcone derivatives: an integrated study for redesigning novel chemical entities as anticancer agents through QSAR, molecular docking, ADMET prediction, and computational simulation
Trupti S. Chitre, Aayush M. Mandot, Ramali D. Bhagwat, et al.
Journal of Biomolecular Structure and Dynamics (2024), pp. 1-24
Closed Access | Times Cited: 1
In silico insights into design of novel VEGFR-2 inhibitors: SMILES-based QSAR modelling, and docking studies on substituted benzo-fused heteronuclear derivatives
Satish C. Gupta, Mrinal Kashyap, Yogita Bansal, et al.
SAR and QSAR in environmental research (2024) Vol. 35, Iss. 4, pp. 265-284
Closed Access | Times Cited: 1
Innovative Strategies for the Quantitative Modeling of Blood-Brain Barrier (BBB) Permeability: Harnessing the Power of Machine Learning-based q-RASAR Approach
Vinay Kumar, Arkaprava Banerjee, Kunal Roy
Molecular Systems Design & Engineering (2024) Vol. 9, Iss. 7, pp. 729-743
Closed Access | Times Cited: 1
An updated overview on nitrogen-rich azole-based gold coordination complexes as potent anticancer agents
Monireh Ghorbanpour, Behzad Soltani
Coordination Chemistry Reviews (2024) Vol. 523, pp. 216233-216233
Closed Access | Times Cited: 1
Selection of optimal validation methods for quantitative structure–activity relationships and applicability domain
Károly Héberger
SAR and QSAR in environmental research (2023) Vol. 34, Iss. 5, pp. 415-434
Open Access | Times Cited: 4
Recent Advances in Machine Learning-Based Chemoinformatics: A Comprehensive Review
Sarfaraz K. Niazi, Zamara Mariam
(2023)
Open Access | Times Cited: 4
Multi-target QSAR modeling for the identification of novel inhibitors against Alzheimer's disease
Vinay Kumar, Achintya Saha, Kunal Roy
Chemometrics and Intelligent Laboratory Systems (2022) Vol. 233, pp. 104734-104734
Closed Access | Times Cited: 7
Multi-target Phenylpropanoids Against Epilepsy
Teresa Carolliny Moreira Lustoza Rodrigues, Arthur Lins Dias, Aline Matilde Ferreira dos Santos, et al.
Current Neuropharmacology (2024) Vol. 22, Iss. 13, pp. 2168-2190
Closed Access
Enhancing fruit SSC detection accuracy via a light attenuation theory-based correction method to mitigate measurement orientation variability
Penghui Liu, Yuanhao Zheng, Hao Tian, et al.
Food Research International (2024) Vol. 196, pp. 115024-115024
Closed Access
Genetic function algorithm (GFA) based QSAR, Molecular Design, and ADMET Screening to assess the antimalarial potential of Amodiaquine derivatives
Zakari Ya’u Ibrahim, Usman Abdulfatai, Stephen Ejeh, et al.
The Microbe (2024), pp. 100208-100208
Open Access
e-QSAR (Explainable AI-QSAR), molecular docking, and ADMET analysis of structurally diverse GSK3-beta modulators to identify concealed modulatory features vindicated by X-ray
Vijay H. Masand, Sami A. Al‐Hussain, Gaurav S. Masand, et al.
Computational Biology and Chemistry (2024) Vol. 115, pp. 108324-108324
Closed Access
In-Silico QSAR Studies of Some Pyrazolone Compounds
Kishor Arora
European Journal of Advanced Chemistry Research (2023) Vol. 4, Iss. 4, pp. 1-8
Open Access | Times Cited: 1
Molecular modelling and machine learning for the investigation of 2-oxazolidinone ribosomal antibacterials
McKenna E. Buckley
(2023)
Open Access
Predictive modeling approaches for the risk assessment of persistent organic pollutants (POPs): from QSAR to machine learning–based models
Prakrity Singh, Shraddha Pandit, Ramakrishnan Parthasarathi
Elsevier eBooks (2023), pp. 77-87
Closed Access
The development and impact of an app for a smart drug interaction reminder system
Hung-Fu Lee, Pei‐Hung Liao
Technology and Health Care (2023) Vol. 32, Iss. 3, pp. 1595-1608
Open Access
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