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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:

Network Inference with Granger Causality Ensembles on Single-Cell Transcriptomic Data
Atul Deshpande, Li‐Fang Chu, Ron Stewart, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2019)
Open Access | Times Cited: 32

Showing 1-25 of 32 citing articles:

A scalable SCENIC workflow for single-cell gene regulatory network analysis
Bram Van de Sande, Christopher Flerin, Kristofer Davie, et al.
Nature Protocols (2020) Vol. 15, Iss. 7, pp. 2247-2276
Closed Access | Times Cited: 907
Benchmarking algorithms for gene regulatory network inference from single-cell transcriptomic data
Aditya Pratapa, Amogh P. Jalihal, Jeffrey Law, et al.
Nature Methods (2020) Vol. 17, Iss. 2, pp. 147-154
Open Access | Times Cited: 578
A comprehensive survey of regulatory network inference methods using single cell RNA sequencing data
Hung Nguyen, Duc Tran, Bang Tran, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 3
Open Access | Times Cited: 135
SERGIO: A Single-Cell Expression Simulator Guided by Gene Regulatory Networks
Payam Dibaeinia, Saurabh Sinha
Cell Systems (2020) Vol. 11, Iss. 3, pp. 252-271.e11
Open Access | Times Cited: 93
From bench to bedside: Single-cell analysis for cancer immunotherapy
Emily F. Davis-Marcisak, Atul Deshpande, Genevieve Stein-O’Brien, et al.
Cancer Cell (2021) Vol. 39, Iss. 8, pp. 1062-1080
Open Access | Times Cited: 85
Machine Intelligence in Single-Cell Data Analysis: Advances and New Challenges
Jiajia Liu, Zhiwei Fan, Weiling Zhao, et al.
Frontiers in Genetics (2021) Vol. 12
Open Access | Times Cited: 56
Network modeling of single-cell omics data: challenges, opportunities, and progresses
Montgomery Blencowe, Douglas Arneson, Jessica Ding, et al.
Emerging Topics in Life Sciences (2019) Vol. 3, Iss. 4, pp. 379-398
Open Access | Times Cited: 58
Benchmarking algorithms for gene regulatory network inference from single-cell transcriptomic data
Aditya Pratapa, Amogh P. Jalihal, Jeffrey Law, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2019)
Open Access | Times Cited: 43
The Importance of Computational Modeling in Stem Cell Research
Antonio del Sol, Sascha Jung
Trends in biotechnology (2020) Vol. 39, Iss. 2, pp. 126-136
Open Access | Times Cited: 38
TENET: gene network reconstruction using transfer entropy reveals key regulatory factors from single cell transcriptomic data
Junil Kim, Simon Toftholm Jakobsen, Kedar Nath Natarajan, et al.
Nucleic Acids Research (2020) Vol. 49, Iss. 1, pp. e1-e1
Open Access | Times Cited: 37
Causal network inference from gene transcriptional time-series response to glucocorticoids
Jonathan Lu, Bianca Dumitrascu, Ian C. McDowell, et al.
PLoS Computational Biology (2021) Vol. 17, Iss. 1, pp. e1008223-e1008223
Open Access | Times Cited: 29
The use of machine learning to discover regulatory networks controlling biological systems
Rossin Erbe, Jessica Gore, Kelly Gemmill, et al.
Molecular Cell (2022) Vol. 82, Iss. 2, pp. 260-273
Open Access | Times Cited: 22
Applying causal discovery to single-cell analyses using CausalCell
Yujian Wen, Jielong Huang, Shuhui Guo, et al.
eLife (2023) Vol. 12
Open Access | Times Cited: 13
Multiscale Network Approaches to Decode the Complexity of Common Human Diseases
Minghui Wang, Yiyuan Liu, Eric Schadt, et al.
Oxford University Press eBooks (2025), pp. 13-28
Closed Access
scTenifoldNet: A Machine Learning Workflow for Constructing and Comparing Transcriptome-wide Gene Regulatory Networks from Single-Cell Data
Daniel Osorio, Yan Zhong, Guanxun Li, et al.
Patterns (2020) Vol. 1, Iss. 9, pp. 100139-100139
Open Access | Times Cited: 32
The future of cerebral organoids in drug discovery
Max R. Salick, Eric Lubeck, Adam J. Riesselman, et al.
Seminars in Cell and Developmental Biology (2020) Vol. 111, pp. 67-73
Closed Access | Times Cited: 26
Inferring better gene regulation networks from single-cell data
Michael P. H. Stumpf
Current Opinion in Systems Biology (2021) Vol. 27, pp. 100342-100342
Closed Access | Times Cited: 20
RVAgene: generative modeling of gene expression time series data
Raktim Mitra, Adam L. MacLean
Bioinformatics (2021) Vol. 37, Iss. 19, pp. 3252-3262
Open Access | Times Cited: 18
Computational systems‐biology approaches for modeling gene networks driving epithelial–mesenchymal transitions
Ataur Katebi, Daniel C. Ramirez, Mingyang Lu
Computational and Systems Oncology (2021) Vol. 1, Iss. 2
Open Access | Times Cited: 16
Gene Regulatory Network Inference using 3D Convolutional Neural Network
Yue Fan, Xiuli Ma
Proceedings of the AAAI Conference on Artificial Intelligence (2021) Vol. 35, Iss. 1, pp. 99-106
Open Access | Times Cited: 15
A single-cell expression simulator guided by gene regulatory networks
Payam Dibaeinia, Saurabh Sinha
bioRxiv (Cold Spring Harbor Laboratory) (2019)
Open Access | Times Cited: 10
A mechanistic simulation of molecular cell states over time
Rossin Erbe, Genevieve Stein-O’Brien, Elana J. Fertig
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 3
Signaling interaction link prediction using deep graph neural networks integrating protein-protein interactions and omics data
Jiarui Feng, Amanda Zeng, Yixin Chen, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2020)
Open Access | Times Cited: 7
Integrated Pipelines for Inferring Gene Regulatory Networks from Single-Cell Data
Aimin Chen, Tianshou Zhou, Tianhai Tian
Current Bioinformatics (2022) Vol. 17, Iss. 7, pp. 559-564
Closed Access | Times Cited: 3
Unveiling gene regulatory networks during cellular state transitions without linkage across time points
Ruosi Wan, Yuhao Zhang, Yongli Peng, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
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