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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:

CORAL: QSAR models of CB1 cannabinoid receptor inhibitors based on local and global SMILES attributes with the index of ideality of correlation and the correlation contradiction index
Parvin Kumar, Ashwani Kumar
Chemometrics and Intelligent Laboratory Systems (2020) Vol. 200, pp. 103982-103982
Closed Access | Times Cited: 50

Showing 26-50 of 50 citing articles:

Identification of good and bad fragments of tricyclic triazinone analogues as potential PKC-θ inhibitors through SMILES–based QSAR and molecular docking
Ashwani Kumar, Parvin Kumar
Structural Chemistry (2020) Vol. 32, Iss. 1, pp. 149-165
Closed Access | Times Cited: 21
The index of ideality of correlation: QSAR studies of hepatitis C virus NS3/4A protease inhibitors using SMILES descriptors
T. Ghiasi, Shahin Ahmadi, Elham Ahmadi, et al.
SAR and QSAR in environmental research (2021) Vol. 32, Iss. 6, pp. 495-520
Closed Access | Times Cited: 18
The System of Self-Consistent of Models: A New Approach to Build Up and Validation of Predictive Models of the Octanol/Water Partition Coefficient for Gold Nanoparticles
Alla P. Toropova, Andrey A. Toropov
International Journal of Environmental Research (2021) Vol. 15, Iss. 4, pp. 709-722
Closed Access | Times Cited: 18
Identifications of good and bad structural fragments of hydrazone/2,5-disubstituted-1,3,4-oxadiazole hybrids with correlation intensity index and consensus modelling using Monte Carlo based QSAR studies, their molecular docking and ADME analysis
Parvin Kumar, Rahul Singh, Ashwani Kumar, et al.
SAR and QSAR in environmental research (2022) Vol. 33, Iss. 9, pp. 677-700
Closed Access | Times Cited: 12
Quantitative structure activity relationship studies of androgen receptor binding affinity of endocrine disruptor chemicals with index of ideality of correlation, their molecular docking, molecular dynamics and ADME studies
Surbhi Goyal, Payal Rani, Monika Chahar, et al.
Journal of Biomolecular Structure and Dynamics (2023) Vol. 41, Iss. 23, pp. 13616-13631
Closed Access | Times Cited: 7
QSTR based on Monte Carlo approach using SMILES and graph features for toxicity toward Tetrahymena pyriformis
Nasrin Rezaie-keikhaie, Fereshteh Shiri, Shahin Ahmadi, et al.
Journal of the Iranian Chemical Society (2023) Vol. 20, Iss. 10, pp. 2609-2620
Closed Access | Times Cited: 7
In silico prediction of the mutagenicity of nitroaromatic compounds using correlation weights of fragments of local symmetry
Andrey A. Toropov, Alla P. Toropova, Alessandra Roncaglioni, et al.
Mutation Research/Genetic Toxicology and Environmental Mutagenesis (2023) Vol. 891, pp. 503684-503684
Closed Access | Times Cited: 7
In-silico identification of fingerprint of pyrazolyl sulfonamide responsible for inhibition of N-myristoyltransferase using Monte Carlo method with index of ideality of correlation
Ashwani Kumar, Jayant Sindhu, Parvin Kumar
Journal of Biomolecular Structure and Dynamics (2020) Vol. 39, Iss. 14, pp. 5014-5025
Open Access | Times Cited: 19
SMILES-based QSAR and molecular docking study of xanthone derivatives as α-glucosidase inhibitors
Shahin Ahmadi, Zohreh Moradi, Ashwani Kumar, et al.
Journal of Receptors and Signal Transduction (2021) Vol. 42, Iss. 4, pp. 361-372
Open Access | Times Cited: 14
SMILES-Based QSAR and Molecular Docking Study of Oseltamivir Derivatives as Influenza Inhibitors
Atena Azimi, Shahin Ahmadi, Ashwani Kumar, et al.
Polycyclic aromatic compounds (2022) Vol. 43, Iss. 4, pp. 3257-3277
Closed Access | Times Cited: 9
Ecotoxicological prediction of organic chemicals toward Pseudokirchneriella subcapitata by Monte Carlo approach
Shahram Lotfi, Shahin Ahmadi, Parvin Kumar
RSC Advances (2022) Vol. 12, Iss. 38, pp. 24988-24997
Open Access | Times Cited: 9
Structural attributes driving λmax towards NIR region: A QSPR approach
Payal Rani, Sandhya Chahal, Priyanka Priyanka, et al.
Chemometrics and Intelligent Laboratory Systems (2024) Vol. 252, pp. 105199-105199
Closed Access | Times Cited: 1
Correlation intensity index-index of ideality of correlation: A hyphenated target function for furtherance of MAO-B inhibitory activity assessment
Bhawna Verma, Sunil Kumar, Parvin Kumar, et al.
Computational Biology and Chemistry (2023) Vol. 108, pp. 107975-107975
Closed Access | Times Cited: 4
In silicoexploration of the fingerprints triggering modulation of glutaminyl cyclase inhibition for the treatment of Alzheimer’s disease using SMILES based attributes in Monte Carlo optimization
Ashwani Kumar, Kiran Bagri, Manisha Nimbhal, et al.
Journal of Biomolecular Structure and Dynamics (2020) Vol. 39, Iss. 18, pp. 7181-7193
Closed Access | Times Cited: 11
Quantitative structure–activity relationship modeling for predication of inhibition potencies of imatinib derivatives using SMILES attributes
Hamideh Hamzehali, Shahram Lotfi, Shahin Ahmadi, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 6
The Role of Endocannabinoid System in Neuroprotection: Molecular Targets and Therapeutic Opportunities
Sonia Thapa, Shashank Singh
Integrative Medicine Reports (2023) Vol. 2, Iss. 1, pp. 72-86
Open Access | Times Cited: 3
Virtual Screening of C. Sativa Constituents for the Identification of Selective Ligands for Cannabinoid Receptor 2
Mikołaj Mizera, Dorota Latek, Judyta Cielecka‐Piontek
International Journal of Molecular Sciences (2020) Vol. 21, Iss. 15, pp. 5308-5308
Open Access | Times Cited: 8
‘Ideal correlations’ for the predictive toxicity to Tetrahymena pyriformis
Andrey A. Toropov, Alla P. Toropova, Emilio Benfenati
Toxicology Mechanisms and Methods (2020) Vol. 30, Iss. 8, pp. 605-610
Closed Access | Times Cited: 6
Development of QSAR Model Based on Monte Carlo Optimization for Predicting GABAA Receptor Binding of Newly Emerging Benzodiazepines
Aleksandra Antović, Radovan Karadžić, Jelena Živković, et al.
Acta chimica slovenica (2023) Vol. 70, Iss. 4, pp. 634-641
Open Access | Times Cited: 2
Semi-correlations as a tool to model for skin sensitization
Alla P. Toropova, Andrey A. Toropov, Emilio Benfenati
Food and Chemical Toxicology (2021) Vol. 157, pp. 112580-112580
Closed Access | Times Cited: 5
Can the Monte Carlo method predict the toxicity of binary mixtures?
Alla P. Toropova, Andrey A. Toropov
Environmental Science and Pollution Research (2021) Vol. 28, Iss. 29, pp. 39493-39500
Closed Access | Times Cited: 4
In silico aquatic toxicity prediction of chemicals towards Daphnia magna and fathead minnow using Monte Carlo approaches
Shahram Lotfi, Shahin Ahmadi, Ali Azimi, et al.
Toxicology Mechanisms and Methods (2024), pp. 1-13
Closed Access
CORAL: Predictions of Quality of Rice Based on Retention Index Using a Combination of Correlation Intensity Index and Consensus Modelling
Parvin Kumar, Ashwani Kumar
Challenges and advances in computational chemistry and physics (2023), pp. 421-462
Closed Access | Times Cited: 1
Predicting the melting point of imidazole-based ionic liquids using QSPR model based on SMILES optimal descriptors
Wen‐Zhen Wang, Bo Yang, Xingang Jia
IOP Conference Series Earth and Environmental Science (2021) Vol. 859, Iss. 1, pp. 012084-012084
Open Access | Times Cited: 2
Application of SMILES to Cheminformatics and Generation of Optimum SMILES Descriptors Using CORAL Software
Andrey A. Toropov, Alla P. Toropova
Challenges and advances in computational chemistry and physics (2023), pp. 57-82
Closed Access
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