Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Deep Transferable Compound Representation across Domains and Tasks for Low Data Drug Discovery
Karim Abbasi, Antti Poso, Jahan B. Ghasemi, et al.
Journal of Chemical Information and Modeling (2019) Vol. 59, Iss. 11, pp. 4528-4539
Closed Access | Times Cited: 44

Showing 1-25 of 44 citing articles:

Transfer Learning for Drug Discovery
Chenjing Cai, Shiwei Wang, Youjun Xu, et al.
Journal of Medicinal Chemistry (2020) Vol. 63, Iss. 16, pp. 8683-8694
Closed Access | Times Cited: 278
DeepCDA: deep cross-domain compound–protein affinity prediction through LSTM and convolutional neural networks
Karim Abbasi, Parvin Razzaghi, Antti Poso, et al.
Bioinformatics (2020) Vol. 36, Iss. 17, pp. 4633-4642
Closed Access | Times Cited: 183
CFSSynergy: Combining Feature-Based and Similarity-Based Methods for Drug Synergy Prediction
Fatemeh Rafiei, Hojjat Zeraati, Karim Abbasi, et al.
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 7, pp. 2577-2585
Closed Access | Times Cited: 26
Current strategies to address data scarcity in artificial intelligence-based drug discovery: A comprehensive review
Amit Gangwal, Azim Ansari, Iqrar Ahmad, et al.
Computers in Biology and Medicine (2024) Vol. 179, pp. 108734-108734
Closed Access | Times Cited: 23
Artificial Intelligence in Drug Discovery: A Comprehensive Review of Data-driven and Machine Learning Approaches
Hyunho Kim, Eun‐Young Kim, Ingoo Lee, et al.
Biotechnology and Bioprocess Engineering (2020) Vol. 25, Iss. 6, pp. 895-930
Open Access | Times Cited: 83
Disrupting 3D printing of medicines with machine learning
Moe Elbadawi, Laura E. McCoubrey, Francesca K. H. Gavins, et al.
Trends in Pharmacological Sciences (2021) Vol. 42, Iss. 9, pp. 745-757
Open Access | Times Cited: 81
Deep Learning in Drug Target Interaction Prediction: Current and Future Perspectives
Karim Abbasi, Parvin Razzaghi, Antti Poso, et al.
Current Medicinal Chemistry (2020) Vol. 28, Iss. 11, pp. 2100-2113
Closed Access | Times Cited: 71
Multimodal brain tumor detection using multimodal deep transfer learning
Parvin Razzaghi, Karim Abbasi, Mahmoud Shirazi, et al.
Applied Soft Computing (2022) Vol. 129, pp. 109631-109631
Closed Access | Times Cited: 40
DeepTraSynergy: drug combinations using multimodal deep learning with transformers
Fatemeh Rafiei, Hojjat Zeraati, Karim Abbasi, et al.
Bioinformatics (2023) Vol. 39, Iss. 8
Open Access | Times Cited: 40
Property-Aware Relation Networks for Few-Shot Molecular Property Prediction
Quanming Yao, Zhenqian Shen, Yaqing Wang, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2024) Vol. 46, Iss. 8, pp. 5413-5429
Open Access | Times Cited: 12
Multi-scale cross-attention transformer via graph embeddings for few-shot molecular property prediction
Luis H.M. Torres, Bernardete Ribeiro, Joel P. Arrais
Applied Soft Computing (2024) Vol. 153, pp. 111268-111268
Open Access | Times Cited: 9
Meta-MolNet: A Cross-Domain Benchmark for Few Examples Drug Discovery
Qiujie Lv, Guanxing Chen, Ziduo Yang, et al.
IEEE Transactions on Neural Networks and Learning Systems (2024) Vol. 36, Iss. 3, pp. 4849-4863
Closed Access | Times Cited: 9
Adapting Deep Learning QSPR Models to Specific Drug Discovery Projects
Andrin Fluetsch, Elena Di Lascio, Grégori Gerebtzoff, et al.
Molecular Pharmaceutics (2024) Vol. 21, Iss. 4, pp. 1817-1826
Closed Access | Times Cited: 8
Data science in unveiling COVID-19 pathogenesis and diagnosis: evolutionary origin to drug repurposing
Jayanta Kumar Das, Giuseppe Tradigo, Pierangelo Veltri, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 2, pp. 855-872
Open Access | Times Cited: 47
Few-shot learning with transformers via graph embeddings for molecular property prediction
Luis H.M. Torres, Bernardete Ribeiro, Joel P. Arrais
Expert Systems with Applications (2023) Vol. 225, pp. 120005-120005
Open Access | Times Cited: 15
Uncertainty-Informed Deep Transfer Learning of Perfluoroalkyl and Polyfluoroalkyl Substance Toxicity
Jeremy Feinstein, Ganesh Sivaraman, Kurt Picel, et al.
Journal of Chemical Information and Modeling (2021) Vol. 61, Iss. 12, pp. 5793-5803
Open Access | Times Cited: 27
BayeshERG: a robust, reliable and interpretable deep learning model for predicting hERG channel blockers
Hyunho Kim, Minsu Park, Ingoo Lee, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 4
Closed Access | Times Cited: 19
Integrating convolutional layers and biformer network with forward-forward and backpropagation training
Ali Kianfar, Parvin Razzaghi, Zahra Asgari
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Data-driven toxicity prediction in drug discovery: Current status and future directions
Ningning Wang, Xinliang David Li, Jing Xiao, et al.
Drug Discovery Today (2024), pp. 104195-104195
Closed Access | Times Cited: 3
The challenges of generalizability in artificial intelligence for ADME/Tox endpoint and activity prediction
David Z Huang, Junaid Baber, Sogole Sami Bahmanyar
Expert Opinion on Drug Discovery (2021) Vol. 16, Iss. 9, pp. 1045-1056
Closed Access | Times Cited: 21
Modality adaptation in multimodal data
Parvin Razzaghi, Karim Abbasi, Mahmoud Shirazi, et al.
Expert Systems with Applications (2021) Vol. 179, pp. 115126-115126
Closed Access | Times Cited: 20
Synthetic repurposing of drugs against hypertension: a datamining method based on association rules and a novel discrete algorithm
Yosef Masoudi-Sobhanzadeh, Ali Masoudi‐Nejad
BMC Bioinformatics (2020) Vol. 21, Iss. 1
Open Access | Times Cited: 18
OptNCMiner: a deep learning approach for the discovery of natural compounds modulating disease-specific multi-targets
Seo Hyun Shin, Seung Man Oh, Jung Han Yoon Park, et al.
BMC Bioinformatics (2022) Vol. 23, Iss. 1
Open Access | Times Cited: 11
NSCGCN: A novel deep GCN model to diagnosis COVID-19
Chaosheng Tang, Chaochao Hu, Junding Sun, et al.
Computers in Biology and Medicine (2022) Vol. 150, pp. 106151-106151
Open Access | Times Cited: 11
A voting-based machine learning approach for classifying biological and clinical datasets
Negar Hossein-Nezhad Daneshvar, Yosef Masoudi-Sobhanzadeh, Yadollah Omidi
BMC Bioinformatics (2023) Vol. 24, Iss. 1
Open Access | Times Cited: 5
Page 1 - Next Page

Scroll to top