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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:

In-silico screening of database for finding potential sweet molecules: A combined data and structure based modeling approach
Anukrati Goel, Kishore Gajula, Rakesh Gupta, et al.
Food Chemistry (2020) Vol. 343, pp. 128538-128538
Closed Access | Times Cited: 20

Showing 20 citing articles:

In-silico investigation of umami peptides with receptor T1R1/T1R3 for the discovering potential targets: A combined modeling approach
Wenli Wang, Zhiyong Cui, Menghua Ning, et al.
Biomaterials (2021) Vol. 281, pp. 121338-121338
Open Access | Times Cited: 78
Application of quantitative structure-activity relationship to food-derived peptides: Methods, situations, challenges and prospects
Weichen Bo, Lang Chen, Dongya Qin, et al.
Trends in Food Science & Technology (2021) Vol. 114, pp. 176-188
Closed Access | Times Cited: 60
Prediction of bitterant and sweetener using structure-taste relationship models based on an artificial neural network
Weichen Bo, Dongya Qin, Xin Zheng, et al.
Food Research International (2022) Vol. 153, pp. 110974-110974
Closed Access | Times Cited: 40
Data-Driven Elucidation of Flavor Chemistry
Xingran Kou, Peiqin Shi, Chukun Gao, et al.
Journal of Agricultural and Food Chemistry (2023) Vol. 71, Iss. 18, pp. 6789-6802
Open Access | Times Cited: 27
Classification-based machine learning approaches to predict the taste of molecules: A review
Cristian Rojas, Davide Ballabio, Viviana Consonni, et al.
Food Research International (2023) Vol. 171, pp. 113036-113036
Open Access | Times Cited: 20
Rethinking Sweetener Discovering: Multiparameter Modeling of Molecular Docking Results between the T1R2–T1R3 Receptor and Compounds with Different Tastes
Zhiyang Zhu, Wei Zhang, Zhenjie Li, et al.
Journal of Agricultural and Food Chemistry (2024) Vol. 72, Iss. 13, pp. 7336-7343
Closed Access | Times Cited: 7
Unlocking the potential of odor-induced sugar reduction: an updated review of the underlying mechanisms, substance selections, and technical methodologies
Lin Zhu, Fei Pan, Felix Stöppelmann, et al.
Trends in Food Science & Technology (2024) Vol. 147, pp. 104423-104423
Open Access | Times Cited: 4
Sensory-guided isolation and identification of new sweet-tasting dammarane-type saponins from Jiaogulan (Gynostemma pentaphyllum) herbal tea
Hongxia Zhang, Zhongze Wang, Zhi‐Zhi Du
Food Chemistry (2022) Vol. 388, pp. 132981-132981
Closed Access | Times Cited: 17
Investigating mechanism of sweetness intensity differences through dynamic analysis of sweetener–T1R2–membrane systems
Yulu Miao, Hui Ni, Xingyi Zhang, et al.
Food Chemistry (2021) Vol. 374, pp. 131807-131807
Closed Access | Times Cited: 21
Sweetener identification using transfer learning and attention mechanism
Fanchao Lin, Yuan Ji, Shoujiang Xu
CyTA - Journal of Food (2024) Vol. 22, Iss. 1
Open Access | Times Cited: 2
Interpretable machine learning methods for in vitro pharmaceutical formulation development
Zhuyifan Ye, Wenmian Yang, Yilong Yang, et al.
Food Frontiers (2021) Vol. 2, Iss. 2, pp. 195-207
Open Access | Times Cited: 17
ChemSweet: An AI-driven computational platform for next-gen sweetener discovery
Jie Qian, Xuejie Wang, Fangliang Song, et al.
Food Chemistry (2024) Vol. 463, pp. 141362-141362
Closed Access | Times Cited: 1
Computational screening of umami tastants using deep learning
Prantar Dutta, Kishore Gajula, Nitu Verma, et al.
Molecular Diversity (2024)
Closed Access | Times Cited: 1
Taste GPCRs and their ligands
Nitzan Dubovski, Fabrizio Fierro, Eitan Margulis, et al.
Progress in molecular biology and translational science (2022), pp. 177-193
Closed Access | Times Cited: 6
Computational screening for new neuroprotective ingredients against Alzheimer's disease from bilberry by cheminformatics approaches
Ran Xiao, Rui Liang, Yunhui Cai, et al.
Frontiers in Nutrition (2022) Vol. 9
Open Access | Times Cited: 3
New Sweet-Tasting Gypenosides from “Jiaogulan” (Gynostemma pentaphyllum) and Their Interactions with the Homology Model of Sweet Taste Receptors
H.J. Zhang, Hui-Wei Zhou, Shou‐Qing Liu, et al.
Journal of Agricultural and Food Chemistry (2024) Vol. 72, Iss. 33, pp. 18619-18629
Closed Access
Prediction of Flavor Potential of Ocimum basilicum L. Side-Stream Phytoconstituents, Using Liquid Chromatography–Tandem Mass Spectrometry Analysis and In Silico Techniques
Eftichia Kritsi, Thalia Tsiaka, Anna Boroboka, et al.
Separations (2024) Vol. 11, Iss. 9, pp. 261-261
Open Access
Classification of Tastants: A Deep Learning Based Approach
Prantar Dutta, Deepak Jain, Rakesh Gupta, et al.
(2023)
Open Access | Times Cited: 1
Classification of Tastants: A Deep Learning Based Approach
Prantar Dutta, Deepak Jain, Rakesh Gupta, et al.
(2022)
Open Access | Times Cited: 2
In-silico investigation of umami peptides with receptor T1R1/T1R3 for the discovering potential targets: A combined modeling approach
Wenli Wang, Zhiyong Cui, Menghua Ning, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2021)
Open Access | Times Cited: 1
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