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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:

PanglaoDB: a web server for exploration of mouse and human single-cell RNA sequencing data
Oscar Franzén, Li‐Ming Gan, Johan Björkegren
Database (2019) Vol. 2019
Open Access | Times Cited: 1173

Showing 1-25 of 1173 citing articles:

TISCH: a comprehensive web resource enabling interactive single-cell transcriptome visualization of tumor microenvironment
Dongqing Sun, Jin Wang, Ya Han, et al.
Nucleic Acids Research (2020) Vol. 49, Iss. D1, pp. D1420-D1430
Open Access | Times Cited: 784
A molecular single-cell lung atlas of lethal COVID-19
Johannes C. Melms, Jana Biermann, Huachao Huang, et al.
Nature (2021) Vol. 595, Iss. 7865, pp. 114-119
Open Access | Times Cited: 589
CellMarker 2.0: an updated database of manually curated cell markers in human/mouse and web tools based on scRNA-seq data
Congxue Hu, Tengyue Li, Yingqi Xu, et al.
Nucleic Acids Research (2022) Vol. 51, Iss. D1, pp. D870-D876
Open Access | Times Cited: 523
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: 491
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: 406
Transfer learning enables predictions in network biology
Christina V. Theodoris, Ling Xiao, Anant Chopra, et al.
Nature (2023) Vol. 618, Iss. 7965, pp. 616-624
Open Access | Times Cited: 379
Pan-cancer characterization of immune-related lncRNAs identifies potential oncogenic biomarkers
Yongsheng Li, Tiantongfei Jiang, Weiwei Zhou, et al.
Nature Communications (2020) Vol. 11, Iss. 1
Open Access | Times Cited: 346
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: 337
A single-cell atlas of chromatin accessibility in the human genome
Kai Zhang, James D. Hocker, Michael Miller, et al.
Cell (2021) Vol. 184, Iss. 24, pp. 5985-6001.e19
Open Access | Times Cited: 327
Accurate estimation of cell composition in bulk expression through robust integration of single-cell information
Brandon Jew, Marcus Alvarez, Elior Rahmani, et al.
Nature Communications (2020) Vol. 11, Iss. 1
Open Access | Times Cited: 315
Interpreting type 1 diabetes risk with genetics and single-cell epigenomics
Joshua Chiou, Ryan J. Geusz, Mei-Lin Okino, et al.
Nature (2021) Vol. 594, Iss. 7863, pp. 398-402
Open Access | Times Cited: 294
Cancer cell states recur across tumor types and form specific interactions with the tumor microenvironment
Dalia Barkley, Reuben Moncada, Maayan Pour, et al.
Nature Genetics (2022) Vol. 54, Iss. 8, pp. 1192-1201
Open Access | Times Cited: 292
scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses
Juexin Wang, Anjun Ma, Yuzhou Chang, et al.
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 288
APOE4 impairs myelination via cholesterol dysregulation in oligodendrocytes
Joel Blanchard, Leyla Anne Akay, José Dávila-Velderrain, et al.
Nature (2022) Vol. 611, Iss. 7937, pp. 769-779
Open Access | Times Cited: 286
Promotion of cholangiocarcinoma growth by diverse cancer-associated fibroblast subpopulations
Silvia Affò, Ajay Nair, Francesco Brundu, et al.
Cancer Cell (2021) Vol. 39, Iss. 6, pp. 866-882.e11
Open Access | Times Cited: 271
scBERT as a large-scale pretrained deep language model for cell type annotation of single-cell RNA-seq data
Fan Yang, Wenchuan Wang, Fang Wang, et al.
Nature Machine Intelligence (2022) Vol. 4, Iss. 10, pp. 852-866
Open Access | Times Cited: 266
Endothelial heterogeneity across distinct vascular beds during homeostasis and inflammation
Ankit Jambusaria, Zhigang Hong, Lianghui Zhang, et al.
eLife (2020) Vol. 9
Open Access | Times Cited: 249
Single-cell RNA sequencing in cardiovascular development, disease and medicine
David T. Paik, Sang-Kyun Cho, Lei Tian, et al.
Nature Reviews Cardiology (2020) Vol. 17, Iss. 8, pp. 457-473
Open Access | Times Cited: 237
Opposing roles of hepatic stellate cell subpopulations in hepatocarcinogenesis
Aveline Filliol, Yoshinobu Saito, Ajay Nair, et al.
Nature (2022) Vol. 610, Iss. 7931, pp. 356-365
Open Access | Times Cited: 196
A curated database reveals trends in single-cell transcriptomics
Valentine Svensson, Eduardo da Veiga Beltrame, Lior Pachter
Database (2020) Vol. 2020
Open Access | Times Cited: 194
Creation of bladder assembloids mimicking tissue regeneration and cancer
Eunjee Kim, Seoyoung Choi, Byunghee Kang, et al.
Nature (2020) Vol. 588, Iss. 7839, pp. 664-669
Closed Access | Times Cited: 191
Automated methods for cell type annotation on scRNA-seq data
Giovanni Pasquini, Jesús Eduardo Rojo Arias, Patrick Schäfer, et al.
Computational and Structural Biotechnology Journal (2021) Vol. 19, pp. 961-969
Open Access | Times Cited: 180
Tutorial: guidelines for annotating single-cell transcriptomic maps using automated and manual methods
Zoe A. Clarke, Tallulah Andrews, Jawairia Atif, et al.
Nature Protocols (2021) Vol. 16, Iss. 6, pp. 2749-2764
Open Access | Times Cited: 159
Computational recognition of lncRNA signature of tumor-infiltrating B lymphocytes with potential implications in prognosis and immunotherapy of bladder cancer
Meng Zhou, Zicheng Zhang, Siqi Bao, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 3
Closed Access | Times Cited: 152
Large-scale integration of single-cell transcriptomic data captures transitional progenitor states in mouse skeletal muscle regeneration
David W. McKellar, Lauren D. Walter, Leo T. Song, et al.
Communications Biology (2021) Vol. 4, Iss. 1
Open Access | Times Cited: 146
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