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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:

MOOMIN: Deep Molecular Omics Network for Anti-Cancer Drug Combination Therapy
Benedek Rózemberczki, Anna Gogleva, Sebastian Nilsson, et al.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management (2022)
Open Access | Times Cited: 15

Showing 15 citing articles:

Multimodal data integration for oncology in the era of deep neural networks: a review
Asim Waqas, Aakash Tripathi, Ravi P. Ramachandran, et al.
Frontiers in Artificial Intelligence (2024) Vol. 7
Open Access | Times Cited: 23
The recent progress of deep-learning-based in silico prediction of drug combination
Haoyang Liu, Zhiguang Fan, Jie Lin, et al.
Drug Discovery Today (2023) Vol. 28, Iss. 7, pp. 103625-103625
Closed Access | Times Cited: 15
A systematic evaluation of deep learning methods for the prediction of drug synergy in cancer
Delora Baptista, Pedro G. Ferreira, Miguel Rocha
PLoS Computational Biology (2023) Vol. 19, Iss. 3, pp. e1010200-e1010200
Open Access | Times Cited: 14
A review on graph neural networks for predicting synergistic drug combinations
Milad Besharatifard, Fatemeh Vafaee
Artificial Intelligence Review (2024) Vol. 57, Iss. 3
Open Access | Times Cited: 4
Phenome-wide identification of therapeutic genetic targets, leveraging knowledge graphs, graph neural networks, and UK Biobank data
Lawrence Middleton, Ioannis N. Melas, Chirag Vasavda, et al.
Science Advances (2024) Vol. 10, Iss. 19
Open Access | Times Cited: 4
RECOVER identifies synergistic drug combinations in vitro through sequential model optimization
Paul A. Bertin, Jarrid Rector-Brooks, Deepak Sharma, et al.
Cell Reports Methods (2023) Vol. 3, Iss. 10, pp. 100599-100599
Open Access | Times Cited: 9
SynerGPT: In-Context Learning for Personalized Drug Synergy Prediction and Drug Design
Carl K. Edwards, Aakanksha Naik, Tushar Khot, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 7
PseAAC2Vec protein encoding for TCR protein sequence classification
Zahra Tayebi, Sarwan Ali, Taslim Murad, et al.
Computers in Biology and Medicine (2024) Vol. 170, pp. 107956-107956
Closed Access | Times Cited: 2
Shift-Robust Molecular Relational Learning with Causal Substructure
Namkyeong Lee, Kanghoon Yoon, Gyoung S. Na, et al.
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2023), pp. 1200-1212
Open Access | Times Cited: 6
When Protein Structure Embedding Meets Large Language Models
Sarwan Ali, Prakash Chourasia, Murray Patterson
Genes (2023) Vol. 15, Iss. 1, pp. 25-25
Open Access | Times Cited: 4
DKPE-GraphSYN: a drug synergy prediction model based on joint dual kernel density estimation and positional encoding for graph representation
Yunyun Dong, Yujie Bai, Haitao Liu, et al.
Frontiers in Genetics (2024) Vol. 15
Open Access | Times Cited: 1
Graph Information Bottleneck-Based Dual Subgraph Prediction for Molecular Interactions
Lanqi Li, Weiming Dong
IEEE Access (2024) Vol. 12, pp. 30113-30122
Open Access
Prediction of anti-cancer drug synergy based on cross-matching network and cancer molecular subtypes
Ran Su, Jingyi Han, Changming Sun, et al.
Computers in Biology and Medicine (2024) Vol. 175, pp. 108441-108441
Closed Access
A systematic evaluation of deep learning methods for the prediction of drug synergy in cancer
Delora Baptista, Pedro G. Ferreira, Miguel Rocha
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 1
BioNE: Integration of network embeddings for supervised learning
Poorya Parvizi, Francisco Azuaje, Evropi Τheodoratou, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access
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