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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:

DeepOlf: Deep Neural Network Based Architecture for Predicting Odorants and Their Interacting Olfactory Receptors
Anju Sharma, Rajnish Kumar, Rahul Semwal, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2020) Vol. 19, Iss. 1, pp. 418-428
Closed Access | Times Cited: 29

Showing 1-25 of 29 citing articles:

SMILES to Smell: Decoding the Structure–Odor Relationship of Chemical Compounds Using the Deep Neural Network Approach
Anju Sharma, Rajnish Kumar, Shabnam Ranjta, et al.
Journal of Chemical Information and Modeling (2021) Vol. 61, Iss. 2, pp. 676-688
Closed Access | Times Cited: 76
Artificial intelligence in intestinal polyp and colorectal cancer prediction
Anju Sharma, Rajnish Kumar, Garima Yadav, et al.
Cancer Letters (2023) Vol. 565, pp. 216238-216238
Closed Access | Times Cited: 24
Deep learning-based prediction model for diagnosing gastrointestinal diseases using endoscopy images
Anju Sharma, Rajnish Kumar, Prabha Garg
International Journal of Medical Informatics (2023) Vol. 177, pp. 105142-105142
Closed Access | Times Cited: 24
Transport features predict if a molecule is odorous
Emily J. Mayhew, Charles J. Arayata, Richard C. Gerkin, et al.
Proceedings of the National Academy of Sciences (2022) Vol. 119, Iss. 15
Open Access | Times Cited: 33
OlfactionBase: a repository to explore odors, odorants, olfactory receptors and odorant–receptor interactions
Anju Sharma, Bishal Kumar Saha, Rajnish Kumar, et al.
Nucleic Acids Research (2021) Vol. 50, Iss. D1, pp. D678-D686
Open Access | Times Cited: 36
Technical Issues in Using Human Olfactory Receptor Responses as a Universal Evaluation Method for Odor and Scent
Shun’ichi Kuroda
Journal of Japan Association on Odor Environment (2025) Vol. 56, Iss. 1, pp. 17-26
Open Access
A deep neural network–based approach for prediction of mutagenicity of compounds
Rajnish Kumar, Farhat Ullah Khan, Anju Sharma, et al.
Environmental Science and Pollution Research (2021) Vol. 28, Iss. 34, pp. 47641-47650
Closed Access | Times Cited: 22
Multi-Omics Approach in the Identification of Potential Therapeutic Biomolecule for COVID-19
Rachana Singh, Pradhyumna Kumar Singh, Rajnish Kumar, et al.
Frontiers in Pharmacology (2021) Vol. 12
Open Access | Times Cited: 21
Recent Applications of Artificial Intelligence in Early Cancer Detection
Nausheen Khanam, Rajnish Kumar
Current Medicinal Chemistry (2022) Vol. 29, Iss. 25, pp. 4410-4435
Closed Access | Times Cited: 14
XGBoost odor prediction model: finding the structure-odor relationship of odorant molecules using the extreme gradient boosting algorithm
Pankaj Tyagi, Anju Sharma, Rahul Semwal, et al.
Journal of Biomolecular Structure and Dynamics (2023) Vol. 42, Iss. 20, pp. 10727-10738
Closed Access | Times Cited: 8
OdoriFy: A conglomerate of artificial intelligence–driven prediction engines for olfactory decoding
Ria Gupta, Aayushi Mittal, V.P. Agrawal, et al.
Journal of Biological Chemistry (2021) Vol. 297, Iss. 2, pp. 100956-100956
Open Access | Times Cited: 18
Human Olfactory Receptor Sensor for Odor Reconstitution
Shun’ichi Kuroda, Yukiko Nakaya-Kishi, Kenji Tatematsu, et al.
Sensors (2023) Vol. 23, Iss. 13, pp. 6164-6164
Open Access | Times Cited: 7
Bridging odorants and olfactory perception through machine learning: A review
Zhong Risheng, Zongliang Ji, Shuqi Wang, et al.
Trends in Food Science & Technology (2024) Vol. 153, pp. 104700-104700
Closed Access | Times Cited: 2
Drawing the Borders of Olfactory Space
Emily J. Mayhew, Charles J. Arayata, Richard C. Gerkin, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2020)
Open Access | Times Cited: 15
Insight into the Structure–Odor Relationship of Molecules: A Computational Study Based on Deep Learning
Weichen Bo, Yuandong Yu, Ran He, et al.
Foods (2022) Vol. 11, Iss. 14, pp. 2033-2033
Open Access | Times Cited: 8
FGFR1Pred: an artificial intelligence-based model for predicting fibroblast growth factor receptor 1 inhibitor
Ekambarapu Sree Charan, Anju Sharma, Hardeep Sandhu, et al.
Molecular Diversity (2023) Vol. 28, Iss. 4, pp. 2065-2076
Closed Access | Times Cited: 4
Deciphering Smells from SMILES Notation of the Chemical Compounds: A Deep Learning Approach
Sakshi Ranjan, Niraj Kumar, Sanjay Kumar Singh
(2024), pp. 538-543
Closed Access | Times Cited: 1
Recent Applications of Artificial Intelligence in the Detection of Gastrointestinal, Hepatic and Pancreatic Diseases
Rajnish Kumar, Farhat Ullah Khan, Anju Sharma, et al.
Current Medicinal Chemistry (2021) Vol. 29, Iss. 1, pp. 66-85
Closed Access | Times Cited: 10
In silico prediction of fragrance retention grades for monomer flavors using QSPR models
Qi Liu, Dehan Luo, Tengteng Wen, et al.
Chemometrics and Intelligent Laboratory Systems (2021) Vol. 218, pp. 104424-104424
Closed Access | Times Cited: 8
Human Olfactory Receptor Sensor for Odor Reconstitution
Shun’ichi Kuroda, Yukiko Nakaya-Kishi, Kenji Tatematsu, et al.
(2023)
Open Access | Times Cited: 3
Remodelling structure-based drug design using machine learning
Shubhankar Dutta, Kakoli Bose
Emerging Topics in Life Sciences (2021) Vol. 5, Iss. 1, pp. 13-27
Closed Access | Times Cited: 7
OBPred: feature-fusion-based deep neural network classifier for odorant-binding protein prediction
Anju Sharma, Rajnish Kumar, Pritish Kumar Varadwaj
Neural Computing and Applications (2021) Vol. 33, Iss. 24, pp. 17633-17646
Closed Access | Times Cited: 7
Intelligent Consensus Predictions of the Retention Index of Flavor and Fragrance Compounds Using 2D Descriptors
Doelima Bera, Ankur Kumar, Joyita Roy, et al.
Chromatographia (2024) Vol. 87, Iss. 9, pp. 581-595
Closed Access
An overview on olfaction in the biological, analytical, computational, and machine learning fields
Federica Chiera, Giosuè Costa, Stefano Alcaro, et al.
Archiv der Pharmazie (2024)
Open Access
AndroPred: an artificial intelligence-based model for predicting androgen receptor inhibitors
Rohit Gagare, Anju Sharma, Prabha Garg
Journal of Biomolecular Structure and Dynamics (2023) Vol. 42, Iss. 14, pp. 7340-7348
Closed Access | Times Cited: 1
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