cellPLATO: an unsupervised method for identifying cell behaviour in heterogeneous cell trajectory data

Shannon, M. J., Eisman, S. E., Lowe, A. R., Sloan, T. F. W., & Mace, E. M. (2024). cellPLATO – an unsupervised method for identifying cell behaviour in heterogeneous cell trajectory data. Journal of Cell Science, 137(20). https://doi.org/10.1242/jcs.261887
Authors:
Michael J. Shannon
Shira E. Eisman
Alan R. Lowe
Tyler F. W. Sloan
Emily M. Mace
Affiliated Authors:
Michael J. Shannon
Shira E. Eisman
Emily M. Mace
Columbia Affiliation:
Subjects:
Killer Cells, Natural (MeSH)
Cell Movement (MeSH)
Interleukin-15 (MeSH)
Advanced Techniques in Bioimage Analysis and Microscopy (OpenAlex Topic)
Comprehensive Integration of Single-Cell Transcriptomic Data (OpenAlex Topic)
Autofocusing in Microscopy and Photography (OpenAlex Topic)
Author Keywords:
key words
nk cells
data-driven analysis
unsupervised machine learning
cell migration
cell morphology
phenomics
il-15
integrins
elink
Publication Type:
Article
Unique ID:
10.1242/jcs.261887
PMID:
38738282
DOI:
10.1242/jcs.261887
Journal:
Journal of Cell Science
Publication Date:
Data Source:
OpenAlex
Source Link:
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