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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:

Current best practices in single‐cell RNA‐seq analysis: a tutorial
Malte D. Luecken, Fabian J. Theis
Molecular Systems Biology (2019) Vol. 15, Iss. 6
Open Access | Times Cited: 1672

Showing 1-25 of 1672 citing articles:

Cells of the adult human heart
Monika Litviňuková, Carlos Talavera‐López, Henrike Maatz, et al.
Nature (2020) Vol. 588, Iss. 7838, pp. 466-472
Open Access | Times Cited: 1205
A single–cell type transcriptomics map of human tissues
Max Karlsson, Cheng Zhang, Loren Méar, et al.
Science Advances (2021) Vol. 7, Iss. 31
Open Access | Times Cited: 1058
SARS‐CoV‐2 receptorACE2 andTMPRSS2 are primarily expressed in bronchial transient secretory cells
Soeren Lukassen, Robert Lorenz Chua, Timo B. Trefzer, et al.
The EMBO Journal (2020) Vol. 39, Iss. 10
Open Access | Times Cited: 965
Microglia states and nomenclature: A field at its crossroads
Rosa Chiara Paolicelli, Amanda Sierra, Beth Stevens, et al.
Neuron (2022) Vol. 110, Iss. 21, pp. 3458-3483
Open Access | Times Cited: 934
Deciphering cell–cell interactions and communication from gene expression
Erick Armingol, Adam Officer, Olivier Harismendy, et al.
Nature Reviews Genetics (2020) Vol. 22, Iss. 2, pp. 71-88
Open Access | Times Cited: 853
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: 824
Benchmarking atlas-level data integration in single-cell genomics
Malte D. Luecken, Maren Büttner, Kridsadakorn Chaichoompu, et al.
Nature Methods (2021) Vol. 19, Iss. 1, pp. 41-50
Open Access | Times Cited: 727
scMC learns biological variation through the alignment of multiple single-cell genomics datasets
Lihua Zhang, Qing Nie
Genome biology (2021) Vol. 22, Iss. 1
Open Access | Times Cited: 643
Integrating single-cell and spatial transcriptomics to elucidate intercellular tissue dynamics
Sophia K. Longo, Margaret Guo, Andrew L. Ji, et al.
Nature Reviews Genetics (2021) Vol. 22, Iss. 10, pp. 627-644
Open Access | Times Cited: 631
Single‐cell RNA sequencing technologies and applications: A brief overview
Dragomirka Jovic, Xue Liang, Zeng Hua, et al.
Clinical and Translational Medicine (2022) Vol. 12, Iss. 3
Open Access | Times Cited: 576
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: 551
MOFA+: a statistical framework for comprehensive integration of multi-modal single-cell data
Ricard Argelaguet, Damien Arnol, Danila Bredikhin, et al.
Genome biology (2020) Vol. 21, Iss. 1
Open Access | Times Cited: 506
A comparison of automatic cell identification methods for single-cell RNA sequencing data
Tamim Abdelaal, Lieke Michielsen, Davy Cats, et al.
Genome biology (2019) Vol. 20, Iss. 1
Open Access | Times Cited: 481
CellRank for directed single-cell fate mapping
Marius Lange, Volker Bergen, Michal Klein, et al.
Nature Methods (2022) Vol. 19, Iss. 2, pp. 159-170
Open Access | Times Cited: 475
The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution
Orit Rozenblatt–Rosen, Aviv Regev, Philipp Oberdoerffer, et al.
Cell (2020) Vol. 181, Iss. 2, pp. 236-249
Open Access | Times Cited: 437
Differential abundance testing on single-cell data using k-nearest neighbor graphs
Emma Dann, Neil C. Henderson, Sarah A. Teichmann, et al.
Nature Biotechnology (2021) Vol. 40, Iss. 2, pp. 245-253
Open Access | Times Cited: 436
Best practices for single-cell analysis across modalities
Lukas Heumos, Anna C. Schaar, Christopher Lance, et al.
Nature Reviews Genetics (2023) Vol. 24, Iss. 8, pp. 550-572
Open Access | Times Cited: 436
Spatiotemporal Immune Landscape of Colorectal Cancer Liver Metastasis at Single-Cell Level
Yingcheng Wu, Shuaixi Yang, Jiaqiang Ma, et al.
Cancer Discovery (2021) Vol. 12, Iss. 1, pp. 134-153
Open Access | Times Cited: 367
SARS-CoV-2 receptor ACE2 and TMPRSS2 are primarily expressed in bronchial transient secretory cells
Soeren Lukassen, Robert Lorenz Chua, Timo B. Trefzer, et al.
The EMBO Journal (2020), pp. e105114-e105114
Closed Access | Times Cited: 367
Fully-automated and ultra-fast cell-type identification using specific marker combinations from single-cell transcriptomic data
Aleksandr Ianevski, Anil K. Giri, Tero Aittokallio
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 358
Regulation of immune responses by the airway epithelial cell landscape
Richard Hewitt, Clare M. Lloyd
Nature reviews. Immunology (2021) Vol. 21, Iss. 6, pp. 347-362
Open Access | Times Cited: 336
High-content CRISPR screening
Christoph Bock, Paul Datlinger, Florence M. Chardon, et al.
Nature Reviews Methods Primers (2022) Vol. 2, Iss. 1
Open Access | Times Cited: 334
SingleCellSignalR: inference of intercellular networks from single-cell transcriptomics
Simon Cabello-Aguilar, Mélissa Alame, Fabien Kon-Sun-Tack, et al.
Nucleic Acids Research (2020) Vol. 48, Iss. 10, pp. e55-e55
Open Access | Times Cited: 324
muscat detects subpopulation-specific state transitions from multi-sample multi-condition single-cell transcriptomics data
Helena L. Crowell, Charlotte Soneson, Pierre‐Luc Germain, et al.
Nature Communications (2020) Vol. 11, Iss. 1
Open Access | Times Cited: 307
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