Additional file 5 of Computational quantification and characterization of independently evolving cellular subpopulations within tumors is critical to inhibit anti-cancer therapy resistance

Additional file 5 of Computational quantification and characterization of independently evolving cellular subpopulations within tumors is critical to inhibit anti-cancer therapy resistance

Additional file 5. Data file of in vivo experiments in the 4T1 system 12 days post RT. The data includes single cell protein expression levels as measured by FACS, lambda (λα(cell)) values and G (Giα) values and % of subpopulations out of the entire population.

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Bibliographische Detailangaben
Hauptverfasser: Alkhatib, Heba, Rubinstein, Ariel M., Vasudevan, Swetha, Flashner-Abramson, Efrat, Stefansky, Shira, Chowdhury, Sangita Roy, Oguche, Solomon, Peretz-Yablonsky, Tamar, Granit, Avital, Granot, Zvi, Ben-Porath, Ittai, Sheva, Kim, Feldman, Jon, Cohen, Noa E., Meirovitz, Amichay, Kravchenko-Balasha, Nataly
Format: Dataset
Sprache:eng
Schlagworte:
Biotechnology
Cancer
Cell Biology
FOS: Biological sciences
FOS: Health sciences
Hematology
Infectious Diseases
Medicine
Pharmacology
Plant Biology
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Beschreibung
Zusammenfassung:Additional file 5. Data file of in vivo experiments in the 4T1 system 12 days post RT. The data includes single cell protein expression levels as measured by FACS, lambda (λα(cell)) values and G (Giα) values and % of subpopulations out of the entire population.
DOI:10.6084/m9.figshare.21376360