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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:

Differentiable biology: using deep learning for biophysics-based and data-driven modeling of molecular mechanisms
Mohammed AlQuraishi, Peter K. Sorger
Nature Methods (2021) Vol. 18, Iss. 10, pp. 1169-1180
Open Access | Times Cited: 70

Showing 1-25 of 70 citing articles:

Glycoproteomics
Ieva Bagdonaite, Stacy A. Malaker, Daniel A. Polasky, et al.
Nature Reviews Methods Primers (2022) Vol. 2, Iss. 1
Open Access | Times Cited: 153
Deep generative molecular design reshapes drug discovery
Xiangxiang Zeng, Fei Wang, Yuan Luo, et al.
Cell Reports Medicine (2022) Vol. 3, Iss. 12, pp. 100794-100794
Open Access | Times Cited: 136
Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies
Rahmad Akbar, Habib Bashour, Puneet Rawat, et al.
mAbs (2022) Vol. 14, Iss. 1
Open Access | Times Cited: 82
In silico proof of principle of machine learning-based antibody design at unconstrained scale
Rahmad Akbar, Philippe A. Robert, Cédric R. Weber, et al.
mAbs (2022) Vol. 14, Iss. 1
Open Access | Times Cited: 75
Biologically informed deep learning to query gene programs in single-cell atlases
Mohammad Lotfollahi, Sergei Rybakov, Karin Hrovatin, et al.
Nature Cell Biology (2023)
Open Access | Times Cited: 57
A new age in protein design empowered by deep learning
Hamed Khakzad, Ilia Igashov, Arne Schneuing, et al.
Cell Systems (2023) Vol. 14, Iss. 11, pp. 925-939
Open Access | Times Cited: 46
Advancing Predictive Risk Assessment of Chemicals via Integrating Machine Learning, Computational Modeling, and Chemical/Nano‐Quantitative Structure‐Activity Relationship Approaches
Ajay Vikram Singh, Mansi Varma, Mansi Rai, et al.
Advanced Intelligent Systems (2024) Vol. 6, Iss. 4
Closed Access | Times Cited: 40
Connectome-constrained networks predict neural activity across the fly visual system
Janne K. Lappalainen, Fabian Tschopp, Sridhama Prakhya, et al.
Nature (2024) Vol. 634, Iss. 8036, pp. 1132-1140
Open Access | Times Cited: 23
Improving Molecular Contrastive Learning via Faulty Negative Mitigation and Decomposed Fragment Contrast
Yuyang Wang, Rishikesh Magar, Liang Chen, et al.
Journal of Chemical Information and Modeling (2022) Vol. 62, Iss. 11, pp. 2713-2725
Open Access | Times Cited: 46
Mechanistic model of MAPK signaling reveals how allostery and rewiring contribute to drug resistance
Fabian Fröhlich, Luca Gerosa, Jeremy Muhlich, et al.
Molecular Systems Biology (2023) Vol. 19, Iss. 2
Open Access | Times Cited: 31
Graph Neural Networks for Molecules
Yuyang Wang, Zijie Li, Amir Barati Farimani
Challenges and advances in computational chemistry and physics (2023), pp. 21-66
Closed Access | Times Cited: 29
Connectome-constrained deep mechanistic networks predict neural responses across the fly visual system at single-neuron resolution
Janne K. Lappalainen, Fabian Tschopp, Sridhama Prakhya, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 25
Differentiable Imaging: A New Tool for Computational Optical Imaging
Ni Chen, Liangcai Cao, Ting‐Chung Poon, et al.
Advanced Physics Research (2023) Vol. 2, Iss. 6
Open Access | Times Cited: 22
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: 7
Insights gained from computational modeling of YAP/TAZ signaling for cellular mechanotransduction
Hamidreza Jafarinia, Ali Khalilimeybodi, Jorge Barrasa‐Fano, et al.
npj Systems Biology and Applications (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 6
AI and precision oncology in clinical cancer genomics: From prevention to targeted cancer therapies-an outcomes based patient care
Zodwa Dlamini, Amanda Skepu, Namkug Kim, et al.
Informatics in Medicine Unlocked (2022) Vol. 31, pp. 100965-100965
Open Access | Times Cited: 25
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
Knowledge-integrated autoencoder model
Teddy Lazebnik, Liron Simon-Keren
Expert Systems with Applications (2024) Vol. 252, pp. 124108-124108
Open Access | Times Cited: 5
Soft Hydrogel Actuator for Fast Machine-Learning-Assisted Bacteria Detection
Filipp V. Lavrentev, Igor S. Rumyantsev, Artemii S. Ivanov, et al.
ACS Applied Materials & Interfaces (2022) Vol. 14, Iss. 5, pp. 7321-7328
Closed Access | Times Cited: 21
Machine Learning for Optical Scanning Probe Nanoscopy
Xinzhong Chen, Suheng Xu, Sara Shabani, et al.
Advanced Materials (2022) Vol. 35, Iss. 34
Open Access | Times Cited: 19
PI3K signaling through a biochemical systems lens
Ralitsa R. Madsen, Alex Toker
Journal of Biological Chemistry (2023) Vol. 299, Iss. 10, pp. 105224-105224
Open Access | Times Cited: 11
Plant science in the age of simulation intelligence
Michiel Stock, Olivier Pieters, Tom De Swaef, et al.
Frontiers in Plant Science (2024) Vol. 14
Open Access | Times Cited: 4
Machine learning in biological physics: From biomolecular prediction to design
Jonathan Martin, M. Mateos, José N. Onuchic, et al.
Proceedings of the National Academy of Sciences (2024) Vol. 121, Iss. 27
Open Access | Times Cited: 4
Fluorescence microscopy and histopathology image based cancer classification using graph convolutional network with channel splitting
Asish Bera, Debotosh Bhattacharjee, Ondřej Krejcar
Biomedical Signal Processing and Control (2025) Vol. 103, pp. 107400-107400
Closed Access
Time series predictions in unmonitored sites: a survey of machine learning techniques in water resources
Jared Willard, Charuleka Varadharajan, Xiaowei Jia, et al.
Environmental Data Science (2025) Vol. 4
Open Access
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