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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:

MSA-Regularized Protein Sequence Transformer toward Predicting Genome-Wide Chemical-Protein Interactions: Application to GPCRome Deorphanization
Tian Cai, Hansaim Lim, Kyra Alyssa Abbu, et al.
Journal of Chemical Information and Modeling (2021) Vol. 61, Iss. 4, pp. 1570-1582
Open Access | Times Cited: 26

Showing 1-25 of 26 citing articles:

Machine Learning Methods for Small Data Challenges in Molecular Science
Bozheng Dou, Zailiang Zhu, Ekaterina Merkurjev, et al.
Chemical Reviews (2023) Vol. 123, Iss. 13, pp. 8736-8780
Open Access | Times Cited: 181
Attention is all you need: utilizing attention in AI-enabled drug discovery
Yang Zhang, Caiqi Liu, Mujiexin Liu, et al.
Briefings in Bioinformatics (2023) Vol. 25, Iss. 1
Open Access | Times Cited: 124
Transformer-based deep learning for predicting protein properties in the life sciences
Abel Chandra, Laura Tünnermann, Tommy Löfstedt, et al.
eLife (2023) Vol. 12
Open Access | Times Cited: 95
Sequence-based drug design as a concept in computational drug design
Lifan Chen, Zisheng Fan, Jie Chang, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 60
Sequence-based prediction of protein binding regions and drug–target interactions
Ingoo Lee, Hojung Nam
Journal of Cheminformatics (2022) Vol. 14, Iss. 1
Open Access | Times Cited: 44
Accelerating Biocatalysis Discovery with Machine Learning: A Paradigm Shift in Enzyme Engineering, Discovery, and Design
Braun Markus, Gruber Christian C, Krassnigg Andreas, et al.
ACS Catalysis (2023) Vol. 13, Iss. 21, pp. 14454-14469
Open Access | Times Cited: 33
Orphan G protein-coupled receptors: the ongoing search for a home
Amie Jobe, Ranjit Vijayan
Frontiers in Pharmacology (2024) Vol. 15
Open Access | Times Cited: 11
Advancing drug discovery with deep attention neural networks
Antonio Lavecchia
Drug Discovery Today (2024) Vol. 29, Iss. 8, pp. 104067-104067
Open Access | Times Cited: 10
GeneralizedDTA: combining pre-training and multi-task learning to predict drug-target binding affinity for unknown drug discovery
Shaofu Lin, Chengyu Shi, Jianhui Chen
BMC Bioinformatics (2022) Vol. 23, Iss. 1
Open Access | Times Cited: 26
Reinforcement learning for systems pharmacology-oriented and personalized drug design
Ryan K. Tan, Yang Liu, Lei Xie
Expert Opinion on Drug Discovery (2022) Vol. 17, Iss. 8, pp. 849-863
Open Access | Times Cited: 25
Explainable artificial intelligence: A taxonomy and guidelines for its application to drug discovery
Ignacio Ponzoni, Juan Antonio Páez Prosper, Nuria E. Campillo
Wiley Interdisciplinary Reviews Computational Molecular Science (2023) Vol. 13, Iss. 6
Closed Access | Times Cited: 16
End-to-end sequence-structure-function meta-learning predicts genome-wide chemical-protein interactions for dark proteins
Tian Cai, Li Xie, Shuo Zhang, et al.
PLoS Computational Biology (2023) Vol. 19, Iss. 1, pp. e1010851-e1010851
Open Access | Times Cited: 14
Deep learning methods for protein structure prediction
Yiming Qin, Zihan Chen, Peng Ye, et al.
MedComm – Future Medicine (2024) Vol. 3, Iss. 3
Open Access | Times Cited: 5
COVID-19 Multi-Targeted Drug Repurposing Using Few-Shot Learning
Yang Liu, You Wu, Xiaoke Shen, et al.
Frontiers in Bioinformatics (2021) Vol. 1
Open Access | Times Cited: 26
Semi-supervised meta-learning elucidates understudied molecular interactions
You Wu, Li Xie, Yang Liu, et al.
Communications Biology (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 3
Gene Target Prediction of Environmental Chemicals Using Coupled Matrix–Matrix Completion
Kai Wang, Nicole J. Kim, Maryam Bagherian, et al.
Environmental Science & Technology (2024) Vol. 58, Iss. 13, pp. 5889-5898
Open Access | Times Cited: 2
DeepREAL: a deep learning powered multi-scale modeling framework for predicting out-of-distribution ligand-induced GPCR activity
Tian Cai, Kyra Alyssa Abbu, Yang Liu, et al.
Bioinformatics (2022) Vol. 38, Iss. 9, pp. 2561-2570
Open Access | Times Cited: 11
Using Sequences of Life-events to Predict Human Lives
Germans Savcisens, Tina Eliassi‐Rad, Lars Kai Hansen, et al.
Research Square (Research Square) (2023)
Open Access | Times Cited: 4
Chemometrics in Quality Control of Traditional Chinese Medicines
Min He, Shaoping Li
(2024), pp. 837-881
Closed Access
SeqDPI: A 1D‐CNN approach for predicting binding affinity of kinase inhibitors
Vinay Priy Mishra, Yogendra Narain Singh, Feroz Khan, et al.
Journal of Computational Chemistry (2024) Vol. 46, Iss. 1
Closed Access
Exploration of Dark Chemical Genomics Space via Portal Learning: Applied to Targeting the Undruggable Genome and COVID-19 Anti-Infective Polypharmacology
Tian Cai, Li Xie, Muge Chen, et al.
Research Square (Research Square) (2021)
Open Access | Times Cited: 3
Refining Embedding-Based Binding Predictions by Leveraging AlphaFold2 Structures
Leopold Endres, Tobias Olenyi, Kyra Erckert, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 2
Model Agnostic Semi-Supervised Meta-Learning Elucidates Understudied Out-of-distribution Molecular Interactions
You Wu, Li Xie, Yang Liu, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access
Drug design and repurposing with a sequence-to-drug paradigm
Lifan Chen, Zisheng Fan, Jie Chang, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access
Semipres: an Integrated Deep Learning Method of Sequence and 3d Object Detection Models for Host-microbe Interactions by Identification of Protein-protein Contact Residues
Hansaim Lim, Özlem Keskin, Ruth Nussinov, et al.
Research Square (Research Square) (2022)
Open Access
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