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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:

Automated cell type discovery and classification through knowledge transfer
Hao-Chih Lee, Roman Kosoy, Christine Becker, et al.
Bioinformatics (2017) Vol. 33, Iss. 11, pp. 1689-1695
Open Access | Times Cited: 68

Showing 1-25 of 68 citing articles:

A comparison framework and guideline of clustering methods for mass cytometry data
Xiao Liu, Weichen Song, Brandon Wong, et al.
Genome biology (2019) Vol. 20, Iss. 1
Open Access | Times Cited: 156
Identification of cell types in multiplexed in situ images by combining protein expression and spatial information using CELESTA
Weiruo Zhang, Irene Li, Nathan E. Reticker-Flynn, et al.
Nature Methods (2022) Vol. 19, Iss. 6, pp. 759-769
Open Access | Times Cited: 84
CyTOF® for the Masses
Akshay Iyer, Anouk A.J. Hamers, Asha Pillai
Frontiers in Immunology (2022) Vol. 13
Open Access | Times Cited: 79
The anatomy of single cell mass cytometry data
Lars Rønn Olsen, Michael D. Leipold, Christina B. Pedersen, et al.
Cytometry Part A (2018) Vol. 95, Iss. 2, pp. 156-172
Open Access | Times Cited: 96
Predicting Cell Populations in Single Cell Mass Cytometry Data
Tamim Abdelaal, Vincent van Unen, Thomas Höllt, et al.
Cytometry Part A (2019) Vol. 95, Iss. 7, pp. 769-781
Open Access | Times Cited: 77
Current trends in flow cytometry automated data analysis software
Melissa Cheung, Jonathan J. Campbell, Liam Whitby, et al.
Cytometry Part A (2021) Vol. 99, Iss. 10, pp. 1007-1021
Open Access | Times Cited: 77
Automated assignment of cell identity from single-cell multiplexed imaging and proteomic data
Michael J. Geuenich, Jinyu Hou, Lee Sunyun, et al.
Cell Systems (2021) Vol. 12, Iss. 12, pp. 1173-1186.e5
Open Access | Times Cited: 59
Different approaches to Imaging Mass Cytometry data analysis
Vladan Milošević
Bioinformatics Advances (2023) Vol. 3, Iss. 1
Open Access | Times Cited: 28
Comprehensive innate immune profiling of chikungunya virus infection in pediatric cases
Daniela Michlmayr, Theodore Pak, Adeeb Rahman, et al.
Molecular Systems Biology (2018) Vol. 14, Iss. 8
Open Access | Times Cited: 71
The impacts of active and self-supervised learning on efficient annotation of single-cell expression data
Michael J. Geuenich, D. H. Gong, Kieran R. Campbell
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 7
MetaCyto: A Tool for Automated Meta-analysis of Mass and Flow Cytometry Data
Zicheng Hu, Chethan Jujjavarapu, Jacob Hughey, et al.
Cell Reports (2018) Vol. 24, Iss. 5, pp. 1377-1388
Open Access | Times Cited: 49
Progress and applications of mass cytometry in sketching immune landscapes
Ting Zhang, Antony R. Warden, Yiyang Li, et al.
Clinical and Translational Medicine (2020) Vol. 10, Iss. 6
Open Access | Times Cited: 44
Recent Advances in Computer-Assisted Algorithms for Cell Subtype Identification of Cytometry Data
Peng Liu, Silvia Liu, Yusi Fang, et al.
Frontiers in Cell and Developmental Biology (2020) Vol. 8
Open Access | Times Cited: 40
VoPo leverages cellular heterogeneity for predictive modeling of single-cell data
Natalie Stanley, Ina A. Stelzer, Amy S. Tsai, et al.
Nature Communications (2020) Vol. 11, Iss. 1
Open Access | Times Cited: 40
A review on deep learning applications in highly multiplexed tissue imaging data analysis
Mohammed Zidane, Ahmad Makky, Matthias Bruhns, et al.
Frontiers in Bioinformatics (2023) Vol. 3
Open Access | Times Cited: 14
Tribus: Semi-automated discovery of cell identities and phenotypes from multiplexed imaging and proteomic data
Ziqi Kang, Angela E. Szabó, Teodora Farago, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 4
CytoPheno: Automated descriptive cell type naming in flow and mass cytometry
Amanda R. Tursi, Celine S. Lages, Kenneth Quayle, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2025)
Open Access
Integrated workflow for analysis of immune enriched spatial proteomic data with IMmuneCite
Arianna Barbetta, Sarah Bangerth, Jason T. C. Lee, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Single-Cell Clustering Based on Shared Nearest Neighbor and Graph Partitioning
Xiaoshu Zhu, Jie Zhang, Yunpei Xu, et al.
Interdisciplinary Sciences Computational Life Sciences (2020) Vol. 12, Iss. 2, pp. 117-130
Closed Access | Times Cited: 32
CyAnno: a semi-automated approach for cell type annotation of mass cytometry datasets
Abhinav Kaushik, Diane Dunham, Ziyuan He, et al.
Bioinformatics (2021) Vol. 37, Iss. 22, pp. 4164-4171
Open Access | Times Cited: 24
Challenges and Adaptations of Model‐Based Clustering for Flow and Mass Cytometry
Ultán P. Doherty, Rachel M. McLoughlin, Arthur White
Wiley Interdisciplinary Reviews Computational Statistics (2025) Vol. 17, Iss. 1
Open Access
Analysis of Single-Cell RNA-seq Data by Clustering Approaches
Xiaoshu Zhu, Hong‐Dong Li, Lilu Guo, et al.
Current Bioinformatics (2018) Vol. 14, Iss. 4, pp. 314-322
Closed Access | Times Cited: 25
Computational flow cytometry provides accurate assessment of measurable residual disease in chronic lymphocytic leukaemia
Phillip Nguyen, Vuong Nguyen, Kylie Baldwin, et al.
British Journal of Haematology (2023) Vol. 202, Iss. 4, pp. 760-770
Closed Access | Times Cited: 7
cytometree: A binary tree algorithm for automatic gating in cytometry analysis
Daniel Commenges, Chariff Alkhassim, Raphaël Gottardo, et al.
Cytometry Part A (2018) Vol. 93, Iss. 11, pp. 1132-1140
Open Access | Times Cited: 23
CytoPy: An autonomous cytometry analysis framework
Ross J. Burton, Raya Ahmed, Simone Cuff, et al.
PLoS Computational Biology (2021) Vol. 17, Iss. 6, pp. e1009071-e1009071
Open Access | Times Cited: 16
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