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Interpretable deep learning of label-free live cell images uncovers functional hallmarks of highly-metastatic melanoma
View ORCID ProfileAssaf Zaritsky, View ORCID ProfileAndrew R. Jamieson, View ORCID ProfileErik S. Welf, View ORCID ProfileAndres Nevarez, Justin Cillay, Ugur Eskiocak, View ORCID ProfileBrandi L. Cantarel, View ORCID ProfileGaudenz Danuser
doi: https://doi.org/10.1101/2020.05.15.096628
Assaf Zaritsky
1Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX 75390, USA
2Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
Andrew R. Jamieson
1Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX 75390, USA
Erik S. Welf
1Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX 75390, USA
Andres Nevarez
1Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX 75390, USA
3Section of Molecular Biology, Division of Biological Sciences, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
Justin Cillay
1Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX 75390, USA
Ugur Eskiocak
4Children’s Research Institute and Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
Brandi L. Cantarel
1Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX 75390, USA
Gaudenz Danuser
1Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX 75390, USA
Article usage
Posted May 15, 2020.
Interpretable deep learning of label-free live cell images uncovers functional hallmarks of highly-metastatic melanoma
Assaf Zaritsky, Andrew R. Jamieson, Erik S. Welf, Andres Nevarez, Justin Cillay, Ugur Eskiocak, Brandi L. Cantarel, Gaudenz Danuser
bioRxiv 2020.05.15.096628; doi: https://doi.org/10.1101/2020.05.15.096628
Interpretable deep learning of label-free live cell images uncovers functional hallmarks of highly-metastatic melanoma
Assaf Zaritsky, Andrew R. Jamieson, Erik S. Welf, Andres Nevarez, Justin Cillay, Ugur Eskiocak, Brandi L. Cantarel, Gaudenz Danuser
bioRxiv 2020.05.15.096628; doi: https://doi.org/10.1101/2020.05.15.096628
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