idr0109
Release Date: 2021-05-31
Publication DOI: 10.1016/j.cels.2021.05.003
Data DOI: 10.17867/10000161
License: CC BY 4.0
PubMed ID: 34077708
External URL: https://github.com/DanuserLab/openLCH
Interpretable deep learning uncovers cellular properties in label-free live cell images that are predictive of highly metastatic melanoma
Live melanoma single cell phase contrast imaging with multiple labels: cell category (PDX, cell line, melanocyte, clonal expansion), PDX metastatic efficiency (high, low, unknown), cell type (e.g. A375, MV3, m405).
Zaritsky A, Jamieson AR, Welf ES, Nevarez A, Cillay J, Eskiocak U, Cantarel BL, Danuser G
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idr0109-zaritsky-melanoma/experimentA ()
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experimentA ( , parquet: )
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Sample Type: cell
Organism: Homo sapiens
Study Type: time-lapse imaging
Imaging Method: phase contrast microscopy
Copyright: Zaritsky et al
Data Publisher: University of Dundee
Annotation File: idr0109-experimentA-annotation.csv
