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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:

Reliable interpretability of biology-inspired deep neural networks
Wolfgang Esser‐Skala, Nikolaus Fortelny
npj Systems Biology and Applications (2023) Vol. 9, Iss. 1
Open Access | Times Cited: 12

Showing 12 citing articles:

Addressing bias in feature importances derived from XGBoost. Comment on Br J Anaesth 2024;133:351–9
Yoshiyasu Takefuji
British Journal of Anaesthesia (2025) Vol. 134, Iss. 2, pp. 613-615
Closed Access | Times Cited: 1
Molecular causality in the advent of foundation models
Sebastian Lobentanzer, Pablo Rodríguez-Mier, Stefan Bauer, et al.
Molecular Systems Biology (2024) Vol. 20, Iss. 8, pp. 848-858
Open Access | Times Cited: 6
Achieving sustainability in heat drying processing: Leveraging artificial intelligence to maintain food quality and minimize carbon footprint
Bara Yudhistira, Prakoso Adi, Rizka Mulyani, et al.
Comprehensive Reviews in Food Science and Food Safety (2024) Vol. 23, Iss. 5
Open Access | Times Cited: 5
Characterizing soil Cops Eco-risk in China
Yan Li, Haoran Huang, Ye Li, et al.
Journal of Hazardous Materials (2025) Vol. 489, pp. 137588-137588
Closed Access
Search direction optimization of power flow analysis based on physics-informed deep learning
Baoliang Li, Qiuwei Wu, Yongji Cao, et al.
International Journal of Electrical Power & Energy Systems (2025) Vol. 167, pp. 110602-110602
Closed Access
Phenotype prediction using biologically interpretable neural networks on multi-cohort multi-omics data
Arno van Hilten, Jeroen van Rooij, Bastiaan T. Heijmans, et al.
npj Systems Biology and Applications (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 2
Inference of drug off-target effects on cellular signaling using interactome-based deep learning
Nikolaos Meimetis, Douglas A. Lauffenburger, A. C. Nilsson
iScience (2024) Vol. 27, Iss. 4, pp. 109509-109509
Open Access | Times Cited: 2
Enhancing data integrity in Electronic Health Records: Review of methods for handling missing data
Amin Vahdati, Sarah Cotterill, Antonia Marsden, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 1
Designing interpretable deep learning applications for functional genomics: a quantitative analysis
Arno van Hilten, Sonja Katz, Edoardo Saccenti, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 5
Open Access | Times Cited: 1
A spatial hierarchical network learning framework for drug repositioning allowing interpretation from macro to micro scale
Zhong-Hao Ren, Xiangxiang Zeng, Yizhen Lao, et al.
Communications Biology (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 1
Improve the interpretability of convolutional neural networks with probability density function
Yueqi Chen, Tingting Pan, Jie Yang
Information Sciences (2024), pp. 121796-121796
Closed Access
Unveiling Neural Networks for Personalized Diet Recommendations
Carlos Cunha, João Rebelo, Rui Pedro Duarte
Procedia Computer Science (2024) Vol. 241, pp. 606-611
Open Access
A Unified Theory of Response Sparsity and Variability for Energy-Efficient Neural Coding
Mingyi Huang, Wei Lin, Anna Wang Roe, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
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