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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:

PerturbNet predicts single-cell responses to unseen chemical and genetic perturbations
Hengshi Yu, Joshua D. Welch
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 14

Showing 14 citing articles:

The specious art of single-cell genomics
Tara Chari, Lior Pachter
PLoS Computational Biology (2023) Vol. 19, Iss. 8, pp. e1011288-e1011288
Open Access | Times Cited: 174
The Specious Art of Single-Cell Genomics
Tara Chari, Lior Pachter
bioRxiv (Cold Spring Harbor Laboratory) (2021)
Open Access | Times Cited: 118
Disentanglement of single-cell data with biolord
Zoe Piran, Niv Cohen, Yedid Hoshen, et al.
Nature Biotechnology (2024)
Open Access | Times Cited: 13
A mini-review on perturbation modelling across single-cell omic modalities
George Gavriilidis, Vasileios Vasileiou, Aspasia Orfanou, et al.
Computational and Structural Biotechnology Journal (2024) Vol. 23, pp. 1886-1896
Open Access | Times Cited: 9
Machine learning to dissect perturbations in complex cellular systems
Pablo Monfort-Lanzas, Katja Rungger, Leonie Madersbacher, et al.
Computational and Structural Biotechnology Journal (2025) Vol. 27, pp. 832-842
Open Access
Transcriptomic forecasting with neural ordinary differential equations
Rossin Erbe, Genevieve Stein-O’Brien, Elana J. Fertig
Patterns (2023) Vol. 4, Iss. 8, pp. 100793-100793
Open Access | Times Cited: 10
Predicting cell morphological responses to perturbations using generative modeling
Alessandro Palma, Fabian J. Theis, Mohammad Lotfollahi
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 9
Autophagy and machine learning: Unanswered questions
Ying Yang, Zhaoying Pan, Jianhui Sun, et al.
Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease (2024) Vol. 1870, Iss. 6, pp. 167263-167263
Closed Access | Times Cited: 2
Multifaceted Representation of Genes via Deep Learning of Gene Expression Networks
Zheng Su, Mingyan Fang, Andrei Smolnikov, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 1
Cell-Graph Compass: Modeling Single Cells with Graph Structure Foundation Model
Chen Fang, Zhilong Hu, Shaole Chang, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 1
Toward subtask-decomposition-based learning and benchmarking for predicting genetic perturbation outcomes and beyond
Yicheng Gao, Zhiting Wei, Kejing Dong, et al.
Nature Computational Science (2024)
Closed Access | Times Cited: 1
Linking transcriptome and morphology in bone cells at cellular resolution with generative AI
Lu Lu, Noriaki Ono, Joshua D. Welch
Journal of Bone and Mineral Research (2024) Vol. 40, Iss. 1, pp. 20-26
Closed Access
BioDSNN: a dual-stream neural network with hybrid biological knowledge integration for multi-gene perturbation response prediction
Yuejun Tan, Linhai Xie, Hong Yang, et al.
Briefings in Bioinformatics (2024) Vol. 26, Iss. 1
Open Access
Transcriptomic forecasting with neural ODEs
Rossin Erbe, Genevieve Stein-O’Brien, Elana J. Fertig
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 2
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